AIMC Topic: Machine Learning

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Representation of molecules for drug response prediction.

Briefings in bioinformatics
The rapid development of machine learning and deep learning algorithms in the recent decade has spurred an outburst of their applications in many research fields. In the chemistry domain, machine learning has been widely used to aid in drug screening...

ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features.

Briefings in bioinformatics
MOTIVATION: The Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. As of CASP14, there are 79 global QA methods, and a minority of 39 residue-level QA methods with very few of them working on protein complex...

Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power.

Briefings in bioinformatics
The trade-off between a machine learning (ML) and deep learning (DL) model's predictability and its interpretability has been a rising concern in central nervous system-related quantitative structure-activity relationship (CNS-QSAR) analysis. Many st...

Machine learning methods, databases and tools for drug combination prediction.

Briefings in bioinformatics
Combination therapy has shown an obvious efficacy on complex diseases and can greatly reduce the development of drug resistance. However, even with high-throughput screens, experimental methods are insufficient to explore novel drug combinations. In ...

Graph representation learning in bioinformatics: trends, methods and applications.

Briefings in bioinformatics
Graph is a natural data structure for describing complex systems, which contains a set of objects and relationships. Ubiquitous real-life biomedical problems can be modeled as graph analytics tasks. Machine learning, especially deep learning, succeed...

A Conceptual Framework to Predict Mental Health Patients' Zoning Classification.

Studies in health technology and informatics
Zoning classification is a rating mechanism, which uses a three-tier color coding to indicate perceived risk from the patients' conditions. It is a widely adopted manual system used across mental health settings, however it is time consuming and cost...

Recent Developments in Artificial Intelligence-Based Techniques for Prostate Cancer Detection: A Scoping Review.

Studies in health technology and informatics
Artificial intelligence (AI) techniques can contribute to the early diagnosis of prostate cancer. Recently, there has been a sharp increase in the literature on AI techniques for prostate cancer diagnosis. This review article presents a summary of th...

Artificial Intelligence Models for Heart Chambers Segmentation from 2D Echocardiographic Images: A Scoping Review.

Studies in health technology and informatics
Echocardiography (echo) is a non-invasive, safe, widely available imaging modality that is frequently used to assess the heart structure and function. Accurate heart chamber segmentation is an essential step to quantify certain parameters, including ...

Developing a Data Driven Approach for Early Detection of SIRS in Pediatric Intensive Care Using Automatically Labeled Training Data.

Studies in health technology and informatics
Critical care can benefit from analyzing data by machine learning approaches for supporting clinical routine and guiding clinical decision-making. Developing data-driven approaches for an early detection of systemic inflammatory response syndrome (SI...

Machine Learning Approaches for Early Prostate Cancer Prediction Based on Healthcare Utilization Patterns.

Studies in health technology and informatics
The goal of this study was to build a machine learning model for early prostate cancer prediction based on healthcare utilization patterns. We examined the frequency and pattern changes of healthcare utilization in 2916 prostate cancer patients 3 yea...