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Development of Machine Learning Models for Predicting Postoperative Delayed Remission in Patients With Cushing's Disease.

The Journal of clinical endocrinology and metabolism Jan 1, 2021
CONTEXT: Postoperative hypercortisolemia mandates further therapy in patients with Cushing's disease (CD). Delayed remission (DR) is defined as not achieving postoperative immediate remission (IR), but having spontaneous remission during long-term fo...
Male Middle Aged China Humans Time Factors Machine Learning Algorithms Treatment Outcome Neurosurgical Procedures Postoperative Period Female Computer Simulation Follow-Up Studies Remission Induction Pituitary ACTH Hypersecretion Reproducibility of Results Models, Statistical ACTH-Secreting Pituitary Adenoma Young Adult Adenoma Prognosis Adult Retrospective Studies
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Confronting pitfalls of AI-augmented molecular dynamics using statistical physics.

The Journal of chemical physics Dec 21, 2020
Artificial intelligence (AI)-based approaches have had indubitable impact across the sciences through the ability to extract relevant information from raw data. Recently, AI has also found use in enhancing the efficiency of molecular simulations, whe...
Molecular Dynamics Simulation Artificial Intelligence Ligands Peptides Protein Conformation Models, Statistical Entropy Proteins
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Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations.

Medicine Dec 11, 2020
Deep learning algorithms have shown excellent performances in the field of medical image recognition, and practical applications have been made in several medical domains. Little is known about the feasibility and impact of an undetectable adversaria...
Humans Neural Networks, Computer Skin Algorithms Reproducibility of Results Skin Diseases Diagnostic Errors Image Interpretation, Computer-Assisted Deep Learning Datasets as Topic Risk Factors Models, Statistical Sensitivity and Specificity
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An approach to predicting patient experience through machine learning and social network analysis.

Journal of the American Medical Informatics Association : JAMIA Dec 9, 2020
OBJECTIVE: Improving the patient experience has become an essential component of any healthcare system's performance metrics portfolio. In this study, we developed a machine learning model to predict a patient's response to the Hospital Consumer Asse...
Electronic Health Records Female Male Surveys and Questionnaires Humans Machine Learning Physician-Patient Relations Patient Satisfaction Patient Outcome Assessment Social Network Analysis ROC Curve Logistic Models Models, Statistical Decision Trees
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Probabilistic forecasting of surgical case duration using machine learning: model development and validation.

Journal of the American Medical Informatics Association : JAMIA Dec 9, 2020
OBJECTIVE: Accurate estimations of surgical case durations can lead to the cost-effective utilization of operating rooms. We developed a novel machine learning approach, using both structured and unstructured features as input, to predict a continuou...
Humans Surgical Procedures, Operative Operating Rooms Operative Time Neural Networks, Computer Models, Statistical Machine Learning Natural Language Processing Forecasting Datasets as Topic Reproducibility of Results
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Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.

Journal of global health Dec 1, 2020
BACKGROUND: Internet search engine data, such as Google Trends, was shown to be correlated with the incidence of COVID-19, but only in several countries. We aim to develop a model from a small number of countries to predict the epidemic alert level i...
Betacoronavirus Pneumonia, Viral Retrospective Studies SARS-CoV-2 Global Health Incidence Models, Statistical Humans Coronavirus Infections Machine Learning Data Accuracy Pandemics Search Engine COVID-19
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An Explainable Artificial Intelligence Predictor for Early Detection of Sepsis.

Critical care medicine Nov 1, 2020
OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed treatment has been associated with an increase in mortality due to irreversible organ damage. This study aimed to develop an explainable artificial inte...
Male Early Diagnosis Middle Aged Humans Sepsis Electronic Health Records Artificial Intelligence Models, Statistical Female Algorithms Risk Factors Retrospective Studies Aged Intensive Care Units
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Synthetic minority oversampling of vital statistics data with generative adversarial networks.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2020
OBJECTIVE: Minority oversampling is a standard approach used for adjusting the ratio between the classes on imbalanced data. However, established methods often provide modest improvements in classification performance when applied to data with extrem...
Vital Statistics Models, Statistical Humans Area Under Curve Neural Networks, Computer Risk ROC Curve Stillbirth
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The Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.

Critical care medicine Nov 1, 2020
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...
Hospitalization Aged Male Middle Aged Bacteremia Blood Culture Models, Statistical Fungemia Electronic Health Records Female Reproducibility of Results Risk Factors Humans Machine Learning Retrospective Studies
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COVID-19 and the epistemology of epidemiological models at the dawn of AI.

Annals of human biology Sep 1, 2020
The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: 'model organisms' chosen for their phylogenetic/aetiological similarities; multivariable...
Knowledge Computer Simulation Humans Betacoronavirus SARS-CoV-2 Artificial Intelligence Pneumonia, Viral Models, Statistical Pandemics Coronavirus Infections COVID-19
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