AIMC Topic: Machine Learning

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Machine learning in RNA structure prediction: Advances and challenges.

Biophysical journal
RNA molecules play a crucial role in various biological processes, with their functionality closely tied to their structures. The remarkable advancements in machine learning techniques for protein structure prediction have shown promise in the field ...

Systematic comparison of 3D Deep learning and classical machine learning explanations for Alzheimer's Disease detection.

Computers in biology and medicine
Black-box deep learning (DL) models trained for the early detection of Alzheimer's Disease (AD) often lack systematic model interpretation. This work computes the activated brain regions during DL and compares those with classical Machine Learning (M...

CCL-DTI: contributing the contrastive loss in drug-target interaction prediction.

BMC bioinformatics
BACKGROUND: The Drug-Target Interaction (DTI) prediction uses a drug molecule and a protein sequence as inputs to predict the binding affinity value. In recent years, deep learning-based models have gotten more attention. These methods have two modul...

Machine Learning and Health Science Research: Tutorial.

Journal of medical Internet research
Machine learning (ML) has seen impressive growth in health science research due to its capacity for handling complex data to perform a range of tasks, including unsupervised learning, supervised learning, and reinforcement learning. To aid health sci...

Machine learning models for predicting unscheduled return visits to an emergency department: a scoping review.

BMC emergency medicine
BACKGROUND: Unscheduled return visits (URVs) to emergency departments (EDs) are used to assess the quality of care in EDs. Machine learning (ML) models can incorporate a wide range of complex predictors to identify high-risk patients and reduce error...

Large-scale proteomics in the first trimester of pregnancy predict psychopathology and temperament in preschool children: an exploratory study.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Understanding the prenatal origins of children's psychopathology is a fundamental goal in developmental and clinical science. Recent research suggests that inflammation during pregnancy can trigger a cascade of fetal programming changes t...

Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Bacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or requ...

Mapping Extracellular Space Features of Viral Encephalitis to Evaluate the Proficiency of Anti-Viral Drugs.

Advanced materials (Deerfield Beach, Fla.)
The extracellular space (ECS) is an important barrier against viral attack on brain cells, and dynamic changes in ECS microstructure characteristics are closely related to the progression of viral encephalitis in the brain and the efficacy of antivir...

ConTIG: Continuous representation learning on temporal interaction graphs.

Neural networks : the official journal of the International Neural Network Society
Representation learning on temporal interaction graphs (TIG) aims to model complex networks with the dynamic evolution of interactions on a wide range of web and social graph applications. However, most existing works on TIG either (a) rely on discre...