Supervised machine learning and associated algorithms: applications in orthopedic surgery
Supervised learning is the most common form of machine learning utilized in medical
research. It is used to predict outcomes of interest or classify positive and/or negative cases …
research. It is used to predict outcomes of interest or classify positive and/or negative cases …
[HTML][HTML] Explainable machine learning techniques to predict amiodarone-induced thyroid dysfunction risk: multicenter, retrospective study with external validation
YT Lu, HJ Chao, YC Chiang, HY Chen - Journal of Medical Internet …, 2023 - jmir.org
Background Machine learning offers new solutions for predicting life-threatening,
unpredictable amiodarone-induced thyroid dysfunction. Traditional regression approaches …
unpredictable amiodarone-induced thyroid dysfunction. Traditional regression approaches …
An analysis of residual financial contagion in Romania's banking market for mortgage loans
The uncertainty of the environment, the complexity of economic systems, both at the national
and global economy levels, and the digital age and artificial intelligence draw attention to …
and global economy levels, and the digital age and artificial intelligence draw attention to …
External validation of models for predicting cumulative live birth over multiple complete cycles of IVF treatment
STUDY QUESTION Can two prediction models developed using data from 1999 to 2009
accurately predict the cumulative probability of live birth per woman over multiple complete …
accurately predict the cumulative probability of live birth per woman over multiple complete …
[HTML][HTML] Technology acceptance prediction of robo-advisors by machine learning
D Chung, P Jeong, D Kwon, H Han - Intelligent Systems with Applications, 2023 - Elsevier
Whether a new technology can spread smoothly in the market heavily depends on the user's
acceptance of the technology. A considerable number of studies have sought to predict user …
acceptance of the technology. A considerable number of studies have sought to predict user …
Using machine learning methods to analyze the association between urinary polycyclic aromatic hydrocarbons and chronic bowel disorders in American adults
X Zang, L Feng, W Qin, W Wang, X Zang - Chemosphere, 2024 - Elsevier
The etiology of chronic bowel disorders is multifaceted, with environmental exposure to
harmful substances potentially playing a significant role in their pathogenesis. However …
harmful substances potentially playing a significant role in their pathogenesis. However …
Machine learning approach for metabolic syndrome diagnosis using explainable data-augmentation-based classification
Metabolic syndrome (MetS) is a cluster of risk factors including hypertension, hyperglycemia,
dyslipidemia, and abdominal obesity. Metabolism-related risk factors include diabetes and …
dyslipidemia, and abdominal obesity. Metabolism-related risk factors include diabetes and …
Estimating postoperative mortality in colorectal surgery-a systematic review of risk prediction models
A Dosis, J Helliwell, A Syversen, J Tiernan… - International Journal of …, 2023 - Springer
Purpose Risk prediction models are frequently used to support decision-making in colorectal
surgery but can be inaccurate. Machine learning (ML) is becoming increasingly popular, and …
surgery but can be inaccurate. Machine learning (ML) is becoming increasingly popular, and …
American college of surgeons NSQIP risk calculator accuracy using a machine learning algorithm compared with regression
Y Liu, CY Ko, BL Hall, ME Cohen - Journal of the American …, 2023 - journals.lww.com
BACKGROUND: The American College of Surgeons NSQIP risk calculator (RC) uses
regression to make predictions for fourteen 30-day surgical outcomes. While this approach …
regression to make predictions for fourteen 30-day surgical outcomes. While this approach …
A machine learning algorithm for peripheral artery disease prognosis using biomarker data
Peripheral artery disease (PAD) biomarkers have been studied in isolation; however, an
algorithm that considers a protein panel to inform PAD prognosis may improve predictive …
algorithm that considers a protein panel to inform PAD prognosis may improve predictive …