AIMC Topic: Machine Learning

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An Educational Review on Machine Learning: A SWOT Analysis for Implementing Machine Learning Techniques in Football.

International journal of sports physiology and performance
PURPOSE: The abundance of data in football presents both opportunities and challenges for decision making. Consequently, this review has 2 primary objectives: first, to provide practitioners with a concise overview of the characteristics of machine-l...

Towards U-Net-based intraoperative 2D dose prediction in high dose rate prostate brachytherapy.

Brachytherapy
BACKGROUND: Poor needle placement in prostate high-dose-rate brachytherapy (HDR-BT) results in sub-optimal dosimetry and mentally predicting these effects during HDR-BT is difficult, creating a barrier to widespread availability of high-quality prost...

Mapping the functional network of human cancer through machine learning and pan-cancer proteogenomics.

Nature cancer
Large-scale omics profiling has uncovered a vast array of somatic mutations and cancer-associated proteins, posing substantial challenges for their functional interpretation. Here we present a network-based approach centered on FunMap, a pan-cancer f...

Machine Learning-Assisted SERS Reveals the Biochemical Signature of Enhanced Protein Secretion from Surface-Modified Magnetic Nanoparticles.

ACS applied materials & interfaces
This study introduces a novel investigation of the interaction between cells and iron oxide-based magnetic nanoparticles (FeO MNPs) via protein secretion and machine learning (ML)-assisted surface-enhanced Raman scattering (SERS). For the first time...

Cyto-Safe: A Machine Learning Tool for Early Identification of Cytotoxic Compounds in Drug Discovery.

Journal of chemical information and modeling
Cytotoxicity is essential in drug discovery, enabling early evaluation of toxic compounds during screenings to minimize toxicological risks. assays support high-throughput screening, allowing for efficient detection of toxic substances while conside...

Antimicrobial Peptides as Broad-Spectrum Therapeutics: Computational Analysis to Identify Universal Physical-Chemical Features Responsible for Multitarget Activity.

The journal of physical chemistry letters
Antimicrobial peptides (AMPs) hold significant potential as broad-spectrum therapeutics due to their ability to target a variety of different pathogens, including bacteria, fungi, and viruses. However, the rational design of these peptides requires t...

PICNIC accurately predicts condensate-forming proteins regardless of their structural disorder across organisms.

Nature communications
Biomolecular condensates are membraneless organelles that can concentrate hundreds of different proteins in cells to operate essential biological functions. However, accurate identification of their components remains challenging and biased towards p...

Performance of automated machine learning in detecting fundus diseases based on ophthalmologic B-scan ultrasound images.

BMJ open ophthalmology
AIM: To evaluate the efficacy of automated machine learning (AutoML) models in detecting fundus diseases using ocular B-scan ultrasound images.

Development and Validation of a Literature Screening Tool: Few-Shot Learning Approach in Systematic Reviews.

Journal of medical Internet research
BACKGROUND: Systematic reviews (SRs) are considered the highest level of evidence, but their rigorous literature screening process can be time-consuming and resource-intensive. This is particularly challenging given the rapid pace of medical advancem...

Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Real-time monitoring of pediatric epileptic seizures poses a significant challenge in clinical practice. In recent years, machine learning (ML) has attracted substantial attention from researchers for diagnosing and treating neurological ...