AIMC Topic: Machine Learning

Clear Filters Showing 3351 to 3360 of 34417 articles

Influence of descriptor database selection on modeling retention factors in capillary micellar and microemulsion electrokinetic chromatography using the solvation parameter model.

Journal of chromatography. A
Abraham's solvation parameter model has been widely used to model retention in capillary micellar and microemulsion electrokinetic chromatography systems. To fit or predict retention factors in separation systems experimentally determined compound de...

An explainable artificial intelligence framework for weaning outcomes prediction using features from electrical impedance tomography.

Computer methods and programs in biomedicine
BACKGROUND: Prolonged mechanical ventilation (PMV) might cause ventilator-associated pneumonia and diaphragmatic injury, and may lead to worsening clinical weaning outcomes. The present study proposes a comprehensive machine learning (ML) framework f...

Real-time health monitoring by examining the role of next-generation elements in a medical app.

Computers in biology and medicine
The healthcare sector is undergoing a profound transformation driven by the rapid rise in healthcare applications (mHealth apps), which are becoming integral to how patients manage their health. This paper examines the role of next-generation technol...

Machine learning-based prediction of bleeding risk in extracorporeal membrane oxygenation patients using transfusion as a surrogate marker.

Transfusion
BACKGROUND: The increasing use of extracorporeal membrane oxygenation (ECMO) has highlighted challenges in managing bleeding complications. Optimal transfusion strategies remain uncertain for this diverse patient group, necessitating accurate predict...

Machine learning approach for optimizing usability of healthcare websites.

Scientific reports
In today's digital era, hospital websites serve as crucial informational resources, providing patients with easy access to medical services. Ensuring the usability of these websites is essential, as it directly impacts users' ability to navigate and ...

A population based optimization of convolutional neural networks for chronic kidney disease prediction.

Scientific reports
Chronic kidney disease (CKD) is a global public health concern, and the timely detection of the disease is priceless. Most of the classical machine learning models have the major drawbacks of being unsophisticated, non-robust, and non-accurate. This ...

Trade-offs between machine learning and deep learning for mental illness detection on social media.

Scientific reports
Social media platforms provide valuable insights into mental health trends by capturing user-generated discussions on conditions such as depression, anxiety, and suicidal ideation. Machine learning (ML) and deep learning (DL) models have been increas...

Machine learning for predicting medical outcomes associated with acute lithium poisoning.

Scientific reports
The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predicting medical outcomes. This study aimed to evaluate the effectiveness of the random forest algorithm ...

The QDπ dataset, training data for drug-like molecules and biopolymer fragments and their interactions.

Scientific data
The development of universal machine learning potentials (MLP) for small organic and drug-like molecules requires large, accurate datasets that span diverse chemical spaces. In this study, we introduce the QDπ dataset which incorporates data taken fr...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study.

JCO clinical cancer informatics
PURPOSE: Anti-PD-1 antibodies are widely used for cancer treatment, including in advanced renal cell carcinoma (RCC). However, the therapeutic response varies among patients. This study aimed to predict tumor response to nivolumab anti-PD-1 antibody ...