AIMC Topic: Machine Learning

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Data - Knowledge driven machine learning model for cancer pain medication decisions.

International journal of medical informatics
BACKGROUND: Cancer pain is one of the most common symptoms in cancer patients, and drug decision-making in cancer pain management remains challenges. This study aims to develop machine learning models using real-world clinical data and prior knowledg...

XGBoost as a reliable machine learning tool for predicting ancestry using autosomal STR profiles - Proof of method.

Forensic science international. Genetics
The aim of this study was to test the validity of a predictive model of ancestry affiliation based on Short Tandem Repeat (STR) profiles. Frequencies of 29 genetic markers from the Promega website for four distinct population groups (African American...

MicroRNA signature for early prediction of knee osteoarthritis structural progression using integrated machine and deep learning approaches.

Osteoarthritis and cartilage
OBJECTIVE: Conventional methodologies are ineffective in predicting the rapid progression of knee osteoarthritis (OA). MicroRNAs (miRNAs) show promise as biomarkers for patient stratification. We aimed to develop a miRNA prognosis model for identifyi...

Development and validation of an artificial intelligence system for surgical case length prediction.

Surgery
BACKGROUND: Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for ...

A Novel Real-time Phase Prediction Network in EEG Rhythm.

Neuroscience bulletin
Closed-loop neuromodulation, especially using the phase of the electroencephalography (EEG) rhythm to assess the real-time brain state and optimize the brain stimulation process, is becoming a hot research topic. Because the EEG signal is non-station...

Ultradense Electrochemical Chip and Machine Learning for High-Throughput, Accurate Anticancer Drug Screening.

ACS sensors
Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of dr...

Identification of Staphylococcus aureus, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii from Raman spectra by Artificial Intelligent Raman Detection and Identification System (AIRDIS) with machine learning.

Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi
BACKGROUND: Rapid and accurate identification of bacteria is required in order to develop effective treatment strategies. Traditional culture-based methods are time-consuming, while MALDI-TOF MS is expensive. The Raman spectroscopy, due to its relati...

Reevaluating feature importances in machine learning models for schizophrenia and bipolar disorder: The need for true associations.

Brain, behavior, and immunity
Skorobogatov et al. developed supervised machine learning models to predict diagnoses and illness states in schizophrenia and bipolar disorder. However, their reliance on bootstrap forests and generalized regressions introduces significant biases in ...

Rational design of potent phosphopeptide binders to endocrine Snk PBD domain by integrating machine learning optimization, molecular dynamics simulation, binding energetics rescoring, and in vitro affinity assay.

European biophysics journal : EBJ
Human Snk is an evolutionarily conserved serine/threonine kinase essential for the maintenance of endocrine stability. The protein consists of a N-terminal catalytic domain and a C-terminal polo-box domain (PBD) that determines subcellular localizati...

Left Atrial Wall Thickness Measured by a Machine Learning Method Predicts AF Recurrence After Pulmonary Vein Isolation.

Journal of cardiovascular electrophysiology
BACKGROUND: Left atrial (LA) remodeling plays a significant role in the progression of atrial fibrillation (AF). Although LA wall thickness (LAWT) has emerged as an indicator of structural remodeling, its impact on AF outcomes remains unclear. We aim...