AIMC Topic: Data Mining

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Enhanced drug-drug interaction extraction from biomedical text using deep learning-based sentence representations.

Scientific reports
The fundamental issue with drug-drug interactions (DDIs) is that they cannot be ignored or overlooked since negative drug reactions and the use of medical services as a result are detrimental to patients and increase healthcare expenses. Conventional...

Development of a prediction model for student teaching satisfaction based on 10 machine learning algorithms.

Scientific reports
Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic performance. Educational evaluation is an important part of the teaching process, and the traditional ev...

MODAPro: Explainable Heterogeneous Networks with Variational Graph Autoencoder for Mining Disease-Specific Functional Molecules and Pathways from Omics Data.

Analytical chemistry
The rapid growth of multiomics data has revolutionized our ability to investigate disease mechanisms, yet significant challenges persist in achieving meaningful integration due to inherent data heterogeneity, characteristic sparsity patterns, and the...

Burden and risk factors of depression in seniors from 1990 to 2021: a multi-database study based on EMR mining methods.

Translational psychiatry
Depression in seniors is a growing public health concern worldwide. Despite the rising prevalence of depression in this demographic, comprehensive data on its burden and trends over an extended period remain limited. This study aims to assess the tre...

Robust comparative evaluation of 15 natural language processing algorithms to positively identify patients with inflammatory bowel disease from secondary care records.

BMJ open gastroenterology
OBJECTIVE: Natural language processing (NLP) can identify cohorts of patients with inflammatory bowel disease (IBD) from free text. However, limited sharing of code, models, and data sets continues to hinder progress. The aim of this study was to eva...

Cardiovascular risk prediction and influencing predictors identification among Bangladeshi individuals using machine learning algorithms and association rule mining.

PloS one
BACKGROUND: Cardiovascular disease (CVD) encompasses a group of disorders that affect the heart and blood vessels, making it one of the leading causes of death globally, including in Bangladesh. Applying predictive modeling for the early identificati...

A foundation model for human-AI collaboration in medical literature mining.

Nature communications
Applying artificial intelligence (AI) for systematic literature review holds great potential for enhancing evidence-based medicine, yet has been limited by insufficient training and evaluation. Here, we present LEADS, an AI foundation model trained o...

A New Approach to Large Multiomics Data Integration.

Analytical chemistry
Data reduction and data mining are common practices for handling large-scale data from wide-ranging sources, but high-dimensional omics and imaging data sets present difficult challenges for feature extraction and data mining due to the large number ...

Data Mining Trauma: AI-Assisted Qualitative Study of Cyber Victimization on Reddit.

JMIR infodemiology
BACKGROUND: Cyber victimization exposes individuals to numerous risks. Developmental and psychological factors may leave some users unaware of the potential dangers, increasing their susceptibility to psychological distress. Despite this vulnerabilit...

Transforming Patient Feedback Into Actionable Insights Through Natural Language Processing: Knowledge Discovery and Action Research Study.

JMIR formative research
BACKGROUND: Patient feedback has emerged as a critical measure of health care quality and a key driver of organizational performance. Traditional manual analysis of unstructured patient feedback presents significant challenges as data volumes grow, m...