AIMC Topic: Machine Learning

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Predicting serious postoperative complications and evaluating racial fairness in machine learning algorithms for metabolic and bariatric surgery.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
BACKGROUND: Predicting the risk of complications is critical in metabolic and bariatric surgery (MBS).

Bayesian learning of feature spaces for multitask regression.

Neural networks : the official journal of the International Neural Network Society
This paper introduces a novel approach to learn multi-task regression models with constrained architecture complexity. The proposed model, named RFF-BLR, consists of a randomised feedforward neural network with two fundamental characteristics: a sing...

FLAT: Fusing layer representations for more efficient transfer learning in NLP.

Neural networks : the official journal of the International Neural Network Society
Parameter efficient transfer learning (PETL) methods provide an efficient alternative for fine-tuning. However, typical PETL methods inject the same structures to all Pre-trained Language Model (PLM) layers and only use the final hidden states for do...

Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy.

Microvascular research
Fluorescence intravital microscopy captures large data sets of dynamic multicellular interactions within various organs such as the lungs, liver, and brain of living subjects. In medical imaging, edge detection is used to accurately identify and deli...

Gender-specific factors of suicidal ideation among high school students in Yunnan province, China: A machine learning approach.

Journal of affective disorders
BACKGROUND: Suicidal ideation (SI) assumes a pivotal role in predicting suicidal behaviors. The incidence of SI among high (junior and senior) school students is significantly higher than that of other age groups. The aim of this study is to explore ...

Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework.

Accident; analysis and prevention
The causes of traffic violations by elderly drivers are different from those of other age groups. To reduce serious traffic violations that are more likely to cause serious traffic crashes, this study divided the severity of traffic violations into t...

Elevating hourly PM forecasting in Istanbul, Türkiye: Leveraging ERA5 reanalysis and genetic algorithms in a comparative machine learning model analysis.

Chemosphere
Rapid urbanization and industrialization have intensified air pollution, posing severe health risks and necessitating accurate PM predictions for effective urban air quality management. This study distinguishes itself by utilizing high-resolution ERA...

Characterization of cardiac resynchronization therapy response through machine learning and personalized models.

Computers in biology and medicine
INTRODUCTION: The characterization and selection of heart failure (HF) patients for cardiac resynchronization therapy (CRT) remain challenging, with around 30% non-responder rate despite following current guidelines. This study aims to propose a nove...