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Proposal of a Method for Transferring High-Quality Scientific Literature Data to Virtual Patient Cases Using Categorical Data Generated by Bernoulli-Distributed Random Values: Development and Prototypical Implementation

Proposal of a Method for Transferring High-Quality Scientific Literature Data to Virtual Patient Cases Using Categorical Data Generated by Bernoulli-Distributed Random Values: Development and Prototypical Implementation

For this purpose, a Bernoulli experiment with the probability p for the occurrence of this symptom is performed, where p is the probability of success (outcome “1”). For example, the coin toss of a fair coin is a Bernoulli experiment with p=1/2 [25], and in our example here, a symptom with the probability p from the literature is given instead.

Christian Schmidt, Dorothea Kesztyüs, Martin Haag, Manfred Wilhelm, Tibor Kesztyüs

JMIR Med Educ 2023;9:e43988

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Health Care Needs of the State: Quantitative Analysis

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Health Care Needs of the State: Quantitative Analysis

For a day-ahead forecast t + n where t= 0 is the last day of observed data, we generated our forecasts as follows: Using a binomial distribution with the success probability equal to DHR(t)', we sampled the number of new hospital admissions yt+n,i using the forecasted number of new confirmed cases θt+n,i on day t+n as the number of trials.

Lauren A Castro, Courtney D Shelley, Dave Osthus, Isaac Michaud, Jason Mitchell, Carrie A Manore, Sara Y Del Valle

JMIR Public Health Surveill 2021;7(6):e27888

Machine Learning Approach to Predict the Probability of Recurrence of Renal Cell Carcinoma After Surgery: Prediction Model Development Study

Machine Learning Approach to Predict the Probability of Recurrence of Renal Cell Carcinoma After Surgery: Prediction Model Development Study

Therefore, it is necessary to predict the probability of RCC recurrence so that risk factors can be managed in advance. The Memorial Sloan Kettering Cancer Center (MSKCC) in the United States developed a nomogram that predicts the probability of recurrence within 5 years using the symptoms and histology of 601 patients with kidney cancer who received surgical treatment in 2001 [14].

HyungMin Kim, Sun Jung Lee, So Jin Park, In Young Choi, Sung-Hoo Hong

JMIR Med Inform 2021;9(3):e25635

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Finally, we provide an interactive, online resource to assess COVID-19 infection probability based on user-defined parameters such as local disease prevalence, imaging, and testing performance [17]. National and state-specific confirmed cases of COVID-19 as of July 2, 2020, were acquired from the Center for Systems Science and Engineering at Johns Hopkins University [18].

Christopher D'Ambrosia, Henrik Christensen, Eliah Aronoff-Spencer

J Med Internet Res 2020;22(12):e24478