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Background: India reported its first Covid-19 case on 30th Jan 2020 with no practically no significant rise noticed in the number of cases in the month of February but March2020 onwards there has been a huge escalation as has been the case with like many other countries the world over. This research paper analyses COVID -19 data initially at a global level and then drills down to the scenario obtained in India. Data is gathered from multiple data sources- several authentic government websites. Variables such as gender, geographical location, age etc. have been represented using Python and Data Visualization techniques. Getting insights on Trend pattern and time series analysis will bring more clarity to the current scenario as analysis is totally on real-time data(till 19th June).
Time Series Analysis and other pattern-recognition techniques are deployed to bring more clarity to the current scenario as analysis is totally based on real-time data(till 19th June,2020) Finally we will use some machine learning algorithms and perform predictive analytics for the near future scenario. We are using a sigmoid model to give an estimate of the day on which we can expect the number of active cases to reach its peak and also when the curve will start to flatten. Strength of Sigmoid model lies in providing a count of date –this is unique feature of analysis in this paper. We are also using certain feature engineering techniques to transfer data into logarithmic scale for better comparison removing any data extremities or outliers. Certain feature engineering techniques have been used to transfer data into logarithmic scale as is affords better comparison removing any data extremities or outliers.
Based on the predictions of the short-term interval, our model can be tuned to forecast long time intervals. Needless to mention there are a lot of factors responsible for the cases to come in the upcoming days. One factor being extent of adherence to the rules and restriction imposed by the Government by the citizens of the country. Objective: Prediction of the number of positive covid cases in the next few months . Methods: Machine Learning Model - Clustering
Sigmoid Model Results: The model predicts maximum active cases at 258846.
The curve flattens by day 154 i.e. 25th September and after that the curve goes down and the number of active cases eventually will decrease. Conclusions: There are a lot of research works going on with respect to vaccines, economic dealings, precautions and reduction of Covid-19 cases. However currently we are at a mid-Covid situation. India along with many other countries are still witnessing upsurge in the number of cases at alarming rates on a daily basis. We have not yet reached the peak. Therefore cuff learning and downward growth are also yet to happen. Each day comes out with fresh information and large amount of data. Also there are many other predictive models using machine learning that beyond the scope of this paper. However at the end of the day it is only the precautionary measures we as responsible citizens can take that will help to flatten the curve. We can all join hands together and maintain all rules and regulations strictly. Maintaining social distancing, taking the lockdown seriously is the only key. This study is based on real time data and will be useful for certain key stakeholders like government officials, healthcare workers to prepare a combat plan along with stringent measures. Also the study will help mathematicians and statisticians to predict outbreak numbers more accurately.
蓝小灯破解版
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2017-02-06
(Toronto, 6 Feb 2017, updated 4 Dec 2017) About a year ago, we calculated a projected impact factor 蓝火丁破解 for i-JMR. We now repeated this exercise for the 2016 impact factor (which can by definition only be calculated in 2017).
The 2016 impact factor of a journal can be calculated as follows (蓝火丁官网):
2016 impact factor = A/B
where:
A = the number of times that all items published in that journal in 2014/15 were cited by indexed publications during 2015.
B = the total number of "citable items" published by that journal in 2014/15.
We are proud to report that the projected impact factor for i-JMR (2016) is 蓝火丁官网, calculated from 84 (citations in 2016) / 37 (citable published articles 2014-2015).
Disclaimer: Calculations are our own and are not provided or endorsed by Clarivate Analytics, the owner of Web of Science and the Journal Citation Reports.
i-JMR is a general medical journal with a focus on innovation in health, health care, and medicine - through new medical techniques and innovative ideas and/or research, including—but not limited to—technology, clinical informatics, sociotechnical and organizational health care innovations, or groundbreaking research.
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i-JMR is also indexed in Clarivate Analytics (formerly the IP and Science Division of Thomson Reuters) new Emerging Sources Citation Index (ESCI).
Background: The United Kingdom has lower survival figures for all types of cancers compared to many European countries despite similar national expenditures on health. This discrepancy may be linked to long diagnostic and treatment delays.
Objective: The aim of this study was to determine whether delays experienced by patients with colorectal cancer (CRC) affect their survival.
蓝火丁破解 This observational study utilized the Somerset Cancer Register to identify patients with CRC who were diagnosed on the basis of positive histology findings. The effects of diagnostic and treatment delays and their subdivisions on outcomes were investigated using Cox proportional hazards regression. Kaplan-Meier plots were used to illustrate group differences.
Results: A total of 648 patients (375 males, 57.9% males) were included in this study. We found that neither diagnostic delay nor treatment delay had an effect on the overall survival in patients with CRC (χ23=1.5, P=.68; χ23=0.6, P=.90, respectively). Similarly, treatment delays did not affect the outcomes in patients with CRC (χ23=5.5, P=.14). The initial Cox regression analysis showed that patients with CRC who had short diagnostic delays were less likely to die than those experiencing long delays (hazard ratio 0.165, 95% CI 0.044-0.616; P=.007). However, this result was nonsignificant following sensitivity analysis.
蓝火丁破解 Diagnostic and treatment delays had no effect on the survival of this cohort of patients with CRC. The utility of the 2-week wait referral system is therefore questioned. Timely screening with subsequent early referral and access to diagnostics may have a more beneficial effect.
The welfare of health care professionals working in hazardous environments is a concerning issue. Personal protective equipment such as face masks, disposable gowns, hair covers, gloves, and shoe covers is often used to prevent contamination from patient contact and droplets. This is especially relevant during an epidemic, when health care professionals are at elevated risk of infection. Failure to provide adequate protection to health care workers during epidemics has medical, ethical, and legal ramifications.
Background: Sepsis is a state of organ dysfunction caused by an impaired host response to infection. It is one of the leading causes of death globally. Sepsis, acute myocardial infarction (AMI), and stroke share the primary management requirement of rapid intervention. This could be achieved through early presentation to the hospital, which demands previous knowledge of the disease to ensure better outcomes.
Objective: Our study aimed to assess the level of public awareness of sepsis compared with AMI and stroke.
Methods: This was a cross-sectional survey study performed in June and July 2018, with 1354 participants from Jeddah, Saudi Arabia, aged ≥18 years. Data entry was performed using Microsoft Excel and statistical analysis including chi-square tests and multilogistic regression was performed using SPSS software.
蓝火丁破解 A total of 1354 participants were included. Only 56.72% (768/1354) had heard of the term “sepsis” and 48.44% (372/768) of these participants were able to correctly identify it. In addition, 88.33% (1196/1354) had heard the term “myocardial infarction” and 64.63% (773/1196) knew the correct definition of that condition. Stroke was recognized by 81.46% (1103/1354) of participants and 59.20% (653/1103) of these participants correctly identified the condition. The difference between those who had heard of these diseases and those who knew the correct definition significantly differed from the values for awareness of sepsis and its definition.
Conclusions: We found that public awareness and knowledge of sepsis are poor amongst the population of Jeddah compared with the awareness and knowledge of AMI and stroke. This lack of knowledge may pose a serious obstruction to the prompt management needed to limit fatal outcomes.
蓝小灯破解版 Bronchial asthma remains a clinical enigma with poorly controlled symptoms or exacerbations despite regular use of inhaled corticosteroids. Home nebulization offers a simplified solution for the delivery of rescue and maintenance bronchodilators, which is especially true for patients with frequent exacerbations during management of uncontrolled or difficult-to-treat asthma.
蓝火丁破解 We aimed to assess the clinical impact and outcomes associated with home nebulization—delivered long-acting bronchodilators for uncontrolled or difficult-to-treat asthma.
Methods: This observational, concurrent study was conducted with 60 patients at 2 centers during November 2018. Statistical analyses for prebronchodilator forced expiratory volume in one second (FEV1) and Global Initiative for Asthma (GINA) asthma control score in patients on long-acting bronchodilators and corticosteroids were conducted, with two-tailed P values <.05 considered statistically significant.
Results: Per protocol analyses (53/60) for consecutive cases receiving home nebulization with long-acting bronchodilators and corticosteroids were conducted. The baseline demographics included a male-to-female ratio of 30:23 and mean values of the following: age, 60.3 years (SD 11.8 years); weight, 64 kg (SD 16.8 kg); FEV1, 43% (SD 16%); GINA asthma control score, 3.0 points (SD 0.8 points); serum eosinophil level, 4% (SD 3%); fractional exhaled nitric oxide (FeNO), 12.1 ppb (SD 6 ppb). Of the patients, 100% (53/53) had uncontrolled symptoms, 69.8% (37/53) had prior exacerbations, 100% (53/53) used formoterol/budesonide, and 75.5% (40/53) used glycopyrronium. The per protocol group (n=53) had significantly improved mean prebronchodilator FEV1 (23.7%, SD 29.8%; 0.46 L, SD 0.58 L; P<.001) and GINA asthma control score (2.1 points, SD 0.8 points, P<.001). At baseline, patients (n=40) receiving glycopyrronium/formoterol/budesonide (25/20/500 mcg) nebulization admixture had the following mean values: prebronchodilator FEV1, 38% (SD 15%); GINA asthma control score, 3.0 points (SD 0.8 points); reversibility, 12% (SD 6%); peripheral eosinophil level, 4% (SD 3%); FeNO, 12 ppb (SD 5.7 ppb). In the post hoc analyses, these patients had significantly improved mean prebronchodilator FEV1 of 27.7% (SD 26.2%; 0.54 L, SD 0.51 L; P<.001) at 8 weeks compared with baseline. At baseline, patients (n=13) receiving formoterol/budesonide (20/500 mcg) nebulization had the following mean values: FEV1, 55% (SD 12%); GINA asthma control score, 3.0 points (SD 1.2 points); reversibility, 14% (SD 7%); serum eosinophil level, 4% (SD 3%); FeNO, 13.3 ppb (SD 6.8 ppb). In the post hoc analyses, these patients showed a significant improvement in prebronchodilator FEV1 of 11.2% (SD 13.1%; 0.22 L, SD 0.25 L; P<.001) from baseline. Breathlessness of mild to moderate intensity was reported by 10 cases (10/53, 18.9%), with no other treatment-emergent adverse events or serious adverse events.
Conclusions: Home nebulization remains a viable option for symptomatic difficult-to-treat asthma cases with frequent use of rescue medications. Glycopyrronium as add-on therapy offers a synergistic response in patients on corticosteroids with difficult-to-treat asthma.
Trial Registration: Clinical Trial Registry of India CTRI/2018/11/016319; http://tinyurl.com/y78cctm3
Background: Medical undergraduates are the future doctors of the country. Therefore, determining how medical students choose their areas of specialty is essential to obtain a balanced distribution of physicians among all specialties. Although gender is a significant factor that affects specialty choice, the factors underlying gender differences in radiology are not fully elucidated.
Objective: This study examined the factors that attracted medical students to and discouraged them from selecting diagnostic radiology and analyzed whether these factors differed between female and male medical students.
Methods: This cross-sectional study conducted at King Abdulaziz University Hospital in Jeddah, Saudi Arabia, used an electronic questionnaire sent to medical students from all medical years during February 2018. Subgroup analyses for gender and radiology interest were performed using the chi-square test and Cramér’s V test.
Results: In total, 539 students (276 women; 263 men) responded. The most common factor preventing students from choosing radiology as a career was the lack of direct patient contact, which deterred approximately 47% who decided against considering this specialty. Negative perceptions by other physicians (P<.001), lack of acknowledgment by patients (P=.004), and lack of structured radiology rotations (P=.007) dissuaded significantly more male students than female students. Among those interested in radiology, more female students were attracted by job flexibility (P=.01), while more male students were attracted by focused patient interactions with minimal paperwork (P<.001).
Conclusions: No significant difference was found between the genders in terms of considering radiology as a specialty. Misconception plays a central role in students’ judgment regarding radiology. Hence, early exposure to radiology, assuming a new teaching method, and using a curriculum that supports the active participation of students in a radiology rotation are needed to overcome this misconception.
Background: Although preference research finds its origins in consumer research, preference elicitation methods have increasingly attracted attention in different decision-making contexts in health care. Simulating real-life decision making is believed to be important during consumer preference elicitation.
蓝火丁官网 The aims of this study were to compare the process of decision making between patients and consumers and to identify methods from the consumer research field that could be applied in patient preference elicitation.
Methods: A narrative literature review was performed to identify preference elicitation concepts from a consumer context that could offer improvements in health care.
Results: The process of decision making between patients and consumers was highly comparable. The following five concepts from the consumer research field that could effectively simulate a real-life decision-making process for applications in health care were identified: simulating alternatives, self-reflection, feedback-driven exploration, separated (adaptive) dual response, and arranging profiles in blocks.
Conclusions: Owing to similarities in the decision-making process, patients could be considered as a subgroup of consumers, suggesting that preference elicitation concepts from the consumer field may be relevant in health care. Five concepts that help to simulate real-life decision making have the potential to improve patient preference elicitation. However, the extent to which real decision-making contexts can be mimicked in health care remains unknown.
Background: Mapping out the research landscape around a project is often time consuming and difficult.
Objective: This study evaluates a commercial artificial intelligence (AI) search engine (IRIS.AI) for its applicability in an automated literature search on a specific medical topic.
Methods: To evaluate the AI search engine in a standardized manner, the concept of a science hackathon was applied. Three groups of researchers were tasked with performing a literature search on a clearly defined scientific project. All participants had a high level of expertise for this specific field of research. Two groups were given access to the AI search engine IRIS.AI. All groups were given the same amount of time for their search and were instructed to document their results. Search results were summarized and ranked according to a predetermined scoring system.
Results: The final scoring awarded 49 and 39 points out of 60 to AI groups 1 and 2, respectively, and the control group received 46 points. A total of 20 scientific studies with high relevance were identified, and 5 highly relevant studies (“spot on”) were reported by each group.
蓝火丁官网 AI technology is a promising approach to facilitate literature searches and the management of medical libraries. In this study, however, the application of AI technology lead to a more focused literature search without a significant improvement in the number of results.
Background: Approximately 50% of patients are nonadherent to prescribed medications. Patient perception regarding medication effectiveness has been linked to improved adherence. However, how patients perceive effectiveness is poorly understood.
Objective: The aim of this study was to elucidate factors associated with perceived treatment satisfaction and effectiveness among patients with chronic health conditions.
Methods: We conducted a descriptive study using a cross-sectional survey design. We administered a Web-based survey to participants with migraine, multiple sclerosis (MS), or rheumatoid arthritis (RA). Patients were recruited from established online communities of Health Union. Descriptive statistics, correlations, and comparison tests were used to examine outcomes.
Results: Data were collected from 1820 patients: 567 with migraine, 717 with MS, and 536 with RA. The majority of participants were female (1644/1820, 90.33%), >40 years old (1462/1820, 80.33%), and diagnosed >5 years ago (1189/1820, 65.33%). Treatment satisfaction and perceived medication effectiveness were highly correlated (r=0.90, P<.01). Overall, three temporal factors were positively correlated with satisfaction or perceived effectiveness: time on current medication (satisfaction rs=0.22, P<.01; effectiveness rs=0.25, P<.01), time since diagnosis (satisfaction rs=0.07, P<.01; effectiveness rs=0.09, P<.01), and time on treatment (effectiveness rs=0.08, P<.01).
Conclusions: Findings validated the strong relationship between treatment satisfaction and perceived effectiveness. Understanding the (1) positive relationship between time and treatment satisfaction and effectiveness and (2) factors associated with determining medication effectiveness can help clinicians better understand the mindset of patients regarding treatment. Clinicians may be better prepared to elicit patient beliefs, which influence medication adherence, for people diagnosed with chronic health conditions.
Background: In Canada, 11.5% to 15.7% of couples suffer from infertility. Anovulation, or failed ovulation, is one of the main causes of infertility in women. In Quebec, the treatment for ovulation induction and other services related to assisted reproductive technology (ART) have been partially reimbursed by the government since 2010.
Objective: This study aimed to compare the willingness to pay (WTP) of women of childbearing age to receive drug treatment in the event of failed ovulation according to 3 different contingent valuation methods.
Methods: The following elicitation techniques were used: simple bid price dichotomous choice (DC), followed by an open-ended question (DC-OE), and a simplified multiple-bounded discrete choice (MBDC). Each participant was randomly assigned to 1 of 3 elicitation techniques. Bid prices ranged from Can $200 to Can $5000. Of the 7 bid prices, 1 was randomly proposed to each participant in the DC and DC-OE groups. For the DC-OE group, if the answer to the DC bid price was no, respondents were asked what was the maximum amount they were willing to pay. For the MBDC group, each respondent was offered an initial bid price of Can $1500, and the subsequent bid price offer increased or decreased according to the answer provided. “蓝小灯破解版” responses were considered as a “no”, and each individual was questioned as to their certainty after each choice. WTP values were estimated using probit and bivariate models; the Welsh and Poe model was also performed for the MBDC group.
Results: The survey was conducted from 2009 to 2010 with a total sample of 680 women. Analyses were performed on 610 respondents (199 DC, 230 DC-OE, and 181 MBDC). Of the 70 respondents who were excluded, 6 did not meet the age criterion, 45 had an annual income less than Can $2500, and 19 did not respond to the WTP question. Mean WTP values were Can $4033.26, Can $1857.90, and Can $1630.63 for DC, DC-OE, and MBDC, respectively. The WTP for MBDC “definitely yes” and “probably yes” values were Can $1516.73 and Can $1871.22, respectively. The 3 elicitation techniques provided WTP value differences that were statistically significant (P<.01). The MBDC was the most accurate method, with a lower confidence interval (Can $557) and a lower (CI/mean) ratio (0.34).
Conclusions: A positive WTP for ovulation induction was found in Quebec. Adding a follow-up question resulted in more accurate WTP values. The MBDC technique provided a more accurate estimate of the WTP with a smaller and, therefore, more efficient confidence interval. To help decision making and improve the effectiveness of the fiscal policy related to the ART program, the WTP value elicited with the MBDC technique should be used.
Background: Optimizing the use of social media to promote hospital branding is important in the present digital era. In Taiwan, only 51.1% of hospitals have official Facebook fan pages. The numbers of likes for these hospitals are also relatively low.
Objective: Our objective was to establish a special branding team for social media operation, led by top administrators of our hospital. Here we present our strategic imperative for promoting hospital branding as well as an analysis of its effectiveness.
蓝火丁官网 Led by top administrators, the branding team was formed by 11 divisions to create branding strategies. From 2016 to 2018, the team implemented action plans. All information unique to the hospital was posted on Facebook, as well as on the hospital’s official website. To determine the plans’ efficiencies, we obtained reference data from Google Analytics, and we compared Facebook Insights reports for 2016 with those for 2017 and 2018.
Results: One of the branding team’s main missions was to establish branding strategies and to integrate segmental branding messages. In each quarter we regularly monitored a total of 52 action plan indicators, including those for process and outcome, and discussed the results at team meetings. We selected 4 main performance outcome indicators to reflect the effectiveness of the branding efforts. Compared with 2016, the numbers of likes posted on the Facebook fan page increased by 61.2% in 2017 and 116.2% in 2018. Similarly, visits to the hospital website increased by 4.8% in 2017 and 33.1% in 2018. Most Facebook fan page and website viewers were in 2 age groups: 25 to 34 years, and 35 to 44 years. Women constituted 60.42% (14,160/23,436) of Facebook fans and 59.39% (778,992/1,311,605) of website viewers. According to the Facebook Insights reports, the number of likes and post sharing both increased in 2017 and 2018, relative to 2016. Comment messages also increased from 2016 to 2018 (P=.02 for the trend). The most common theme of posts varied over time, from media reports in 2016, to innovative services in both 2017 and 2018. Likes for innovative services posts increased from 2016 through 2018 (P=.045 for the trend). By the end of 2018, we recorded 23,436 cumulative likes for posts, the highest number among medical centers in Taiwan.
Conclusions: We achieved the largest number of Facebook fans among all medical centers in Taiwan. We would like to share our experience with other hospitals that might be interested in engaging in social media for future communications and interactions with their patients.
Background: Epilepsy is a chronic disease characterized by periodic seizures that result from abnormal integrated firing impulses in the brain. It is one of the most common neurological disorders. Over the past few years, there has been increasing awareness about the effect that having a child with epilepsy has on parents and the reciprocal impact of parental knowledge and attitudes regarding epilepsy on the affected child.
Objective: This study aimed to assess parental knowledge, attitudes, and behavior toward their epileptic children.
Methods: A cross-sectional study was conducted in 2018 by the Pediatric Neurology Department of King Abdulaziz University Hospital, Jeddah, the Kingdom of Saudi Arabia. A sample size of 115 of 332 parents who have a child diagnosed with epilepsy and aged 18 years or younger were recruited for this study. Statistical analysis was performed using SPSS version 21. Data analysis was performed using an independent t test, a chi-square test, one-way analysis of variance, and correlation analysis.
蓝小灯破解版 A total of 115 participants answered the questionnaire; of these, 65 (56.5%) were men, with an average age of 40.3 years, and the mean age of the children was 9.0 years. Overall, 85 (85/115, 73.9%) children were taken care of by both of their parents. The mean parental knowledge score was 7.49 (SD 2.08) out of 12, and it was significantly related to the educational level of the parent (P=.004). The knowledge question that was most frequently answered incorrectly was “Diagnosis of epilepsy is usually made based on at least two unprovoked seizures.” As only 28.7% (33/115) of participants chose the correct answer, mean parental attitude score was 26.51 (SD 4.284) out of 35, and there was no significant relation with the educational level of parents (P=.13); however, it was negatively correlated with the child’s age (P=.045). Mean parental behavioral score was 23.35 (SD 4.121) out of 35, and there was no significant relation with the educational level of the parents (P=.24). The most negatively answered question for the behavior section was “I can leave my child without supervision,” with a mean score of 2.25 (SD 1.09) out of 5. Gender did not play a significant role in parental knowledge, attitudes, or behavior (P=.44, P=.77, and P=.99, respectively).
Conclusions: Parental knowledge in our sample still needs improvement. Therefore, more awareness campaigns should be made for the community and for the parents of affected children to create a supportive environment for the children and help them thrive and develop.
Background: A minimum standard based upon consensus decision making recommends a core set of tinnitus-specific health complaints (outcome domains) that should be assessed and reported in all clinical trials as this enables comparisons to be made across studies as well as data pooling for meta-analysis.
Objective: This study aimed to further clarify how the outcome domain concepts should be defined for 5 of the core set: tinnitus intrusiveness, sense of control, acceptance of tinnitus, concentration, and ability to ignore. This step requires a clear and fully elaborated definition for each outcome domain, moving from an abstract or a vague concept to an operationalized and measurable health-related construct, so that a suitable measurement instrument can then be identified.
Methods: A series of 5 focus group–style semistructured discussions were conducted via a Web-based discussion forum, each open for 2 weeks and ending with a vote. The participants included 148 tinnitus experts who completed a preceding e-Delphi survey that had generated the original set of minimum standards. The participants were health care users living with tinnitus, health care professionals, clinical researchers, commercial representatives, and funders.
Results: The Web discussions led to a revision of all 5 original plain language definitions that had been used in the preceding e-Delphi survey. Each revised definition was voted by 8 to 53 participants and reached the prespecified threshold of 70% consensus for all except tinnitus intrusiveness. Although a single definition was not agreed upon for tinnitus intrusiveness, the majority of participants shared the view that the concept should be sufficiently broad to encapsulate a range of subdomains. The examples included tinnitus awareness, unpleasantness, and impact on different aspects of everyday life. Thematic analysis of the 5 Web-based discussion threads gave important insights into expert interpretations of each core outcome domain, generating an operationalized and measurable health construct in each case.
Conclusions: The qualitative data gathered during the Web-based discussion forum provided an important in-depth understanding of the health concepts that had raised a debate during earlier face-to-face meetings. The descriptive summaries and definitions provide sufficient operationalization of those concepts to proceed to the second stage of core outcome set development that is to identify and evaluate suitable measurement instruments. This study supports the use of Web-based peer discussion forums in defining health concepts.
Background: India reported its first Covid-19 case on 30th Jan 2020 with no practically no significant rise noticed in the number of cases in the month of February but March2020 onwards there has been a huge escalation as has been the case with like many other countries the world over. This research paper analyses COVID -19 data initially at a global level and then drills down to the scenario obtained in India. Data is gathered from multiple data sources- several authentic government websites. Variables such as gender, geographical location, age etc. have been represented using Python and Data Visualization techniques. Getting insights on Trend pattern and time series analysis will bring more clarity to the current scenario as analysis is totally on real-time data(till 19th June).
Time Series Analysis and other pattern-recognition techniques are deployed to bring more clarity to the current scenario as analysis is totally based on real-time data(till 19th June,2020) Finally we will use some machine learning algorithms and perform predictive analytics for the near future scenario. We are using a sigmoid model to give an estimate of the day on which we can expect the number of active cases to reach its peak and also when the curve will start to flatten. Strength of Sigmoid model lies in providing a count of date –this is unique feature of analysis in this paper. We are also using certain feature engineering techniques to transfer data into logarithmic scale for better comparison removing any data extremities or outliers. Certain feature engineering techniques have been used to transfer data into logarithmic scale as is affords better comparison removing any data extremities or outliers.
Based on the predictions of the short-term interval, our model can be tuned to forecast long time intervals. Needless to mention there are a lot of factors responsible for the cases to come in the upcoming days. One factor being extent of adherence to the rules and restriction imposed by the Government by the citizens of the country. Objective: Prediction of the number of positive covid cases in the next few months . Methods: Machine Learning Model - Clustering
Sigmoid Model Results: The model predicts maximum active cases at 258846.
The curve flattens by day 154 i.e. 25th September and after that the curve goes down and the number of active cases eventually will decrease. Conclusions: There are a lot of research works going on with respect to vaccines, economic dealings, precautions and reduction of Covid-19 cases. However currently we are at a mid-Covid situation. India along with many other countries are still witnessing upsurge in the number of cases at alarming rates on a daily basis. We have not yet reached the peak. Therefore cuff learning and downward growth are also yet to happen. Each day comes out with fresh information and large amount of data. Also there are many other predictive models using machine learning that beyond the scope of this paper. However at the end of the day it is only the precautionary measures we as responsible citizens can take that will help to flatten the curve. We can all join hands together and maintain all rules and regulations strictly. Maintaining social distancing, taking the lockdown seriously is the only key. This study is based on real time data and will be useful for certain key stakeholders like government officials, healthcare workers to prepare a combat plan along with stringent measures. Also the study will help mathematicians and statisticians to predict outbreak numbers more accurately.
