AIMC Topic: Sex Factors
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Predicting sex from retinal fundus photographs using automated deep learning.
Scientific reports
May 13, 2021
Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. Herein we present the development of a deep learning model by clinicians without coding, which predicts reporte...
A Comparison of an Artificial Intelligence Tool to Fundamental Frequency as an Outcome Measure in People Seeking a More Feminine Voice.
The Laryngoscope
May 11, 2021
OBJECTIVES/HYPOTHESIS: An artificial intelligence (AI) tool was developed using audio clips of cis-male and cis-female voices based on spectral analysis to assess %probability of a voice being perceived as female (%Prob♀). This program was validated ...
Artificial Intelligence for Unstructured Healthcare Data: Application to Coding of Patient Reporting of Adverse Drug Reactions.
Clinical pharmacology and therapeutics
May 8, 2021
Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its input will, however, only be optimized if systems can manage to deal with its tremendous flow of information, based primarily on unstructured text fields. The a...
Sex-Specific Classification of Drug-Induced Torsade de Pointes Susceptibility Using Cardiac Simulations and Machine Learning.
Clinical pharmacology and therapeutics
Apr 19, 2021
Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidelines require quantification of hERG channel block in vitro and QT interval prolongation in vivo for ...
Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification.
European journal of cancer (Oxford, England : 1990)
Apr 7, 2021
BACKGROUND: Clinicians and pathologists traditionally use patient data in addition to clinical examination to support their diagnoses.
Pharmacokinetics of Eltrombopag in Healthy Chinese Subjects and Effect of Sex and Genetic Polymorphism on its Pharmacokinetic and Pharmacodynamic Variability.
European journal of drug metabolism and pharmacokinetics
Mar 29, 2021
BACKGROUND AND OBJECTIVE: Eltrombopag is the first oral, small-molecule, non-peptide thrombopoietin receptor agonist for the treatment of idiopathic thrombocytopenic purpura. This study investigated the pharmacokinetics of eltrombopag in healthy Chin...
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.
Scientific reports
Feb 5, 2021
Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic m...
Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.
Scientific reports
Feb 3, 2021
COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and has caused huge losses to people's health. Acute respiratory distress syndrome (ARDS) is one of the common clinical manifestations of severe COVID-19 ...
Physical Features and Vital Signs Predict Serum Albumin and Globulin Concentrations Using Machine Learning.
Asian Pacific journal of cancer prevention : APJCP
Feb 1, 2021
OBJECTIVE: Serum protein concentrations are diagnostically and prognostically valuable in cancer and other diseases, but their measurement via blood test is uncomfortable, inconvenient, and costly. This study investigates the possibility of predictin...
Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably.
Journal of clinical epidemiology
Jan 22, 2021
OBJECTIVE: The objective of the study was to compare the performance of logistic regression and boosted trees for predicting patient mortality from large sets of diagnosis codes in electronic healthcare records.
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