AIMC Topic: Databases, Factual

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American College of Surgeons survival calculator for biliary tract cancers: using machine learning to individualize predictions.

Surgery
BACKGROUND: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American College of Surgeons "Biliary Tract Cancer Survival Calculator" prototype using machine learning to g...

Interaction effect between data discretization and data resampling for class-imbalanced medical datasets.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundData discretization is an important preprocessing step in data mining for the transfer of continuous feature values to discrete ones, which allows some specific data mining algorithms to construct more effective models and facilitates the d...

Detection of retinal diseases using an accelerated reused convolutional network.

Computers in biology and medicine
Convolutional neural networks are continually evolving; with some efforts aimed at improving accuracy, others at increasing speed, and some at enhancing accessibility. Improving accessibility broadens the application of neural networks across a wider...

PhenoFlow: A Human-LLM Driven Visual Analytics System for Exploring Large and Complex Stroke Datasets.

IEEE transactions on visualization and computer graphics
Acute stroke demands prompt diagnosis and treatment to achieve optimal patient outcomes. However, the intricate and irregular nature of clinical data associated with acute stroke, particularly blood pressure (BP) measurements, presents substantial ob...

Towards Dataset-Scale and Feature-Oriented Evaluation of Text Summarization in Large Language Model Prompts.

IEEE transactions on visualization and computer graphics
Recent advancements in Large Language Models (LLMs) and Prompt Engineering have made chatbot customization more accessible, significantly reducing barriers to tasks that previously required programming skills. However, prompt evaluation, especially a...

BalancerGNN: Balancer Graph Neural Networks for imbalanced datasets: A case study on fraud detection.

Neural networks : the official journal of the International Neural Network Society
Fraud detection for imbalanced datasets is challenging due to machine learning models inclination to learn the majority class. Imbalance in fraud detection datasets affects how graphs are built, an important step in many Graph Neural Networks (GNNs)....

Improved facial emotion recognition model based on a novel deep convolutional structure.

Scientific reports
Facial Emotion Recognition (FER) is a very challenging task due to the varying nature of facial expressions, occlusions, illumination, pose variations, cultural and gender differences, and many other aspects that cause a drastic degradation in qualit...

Exploring the Potential of Adaptive, Local Machine Learning in Comparison to the Prediction Performance of Global Models: A Case Study from Bayer's Caco-2 Permeability Database.

Journal of chemical information and modeling
Machine learning (ML) techniques are being widely implemented to fill the gap in simple molecular design guidelines for newer therapeutic modalities in the extended and beyond rule of five chemical space (eRo5, bRo5). These ML techniques predict mole...

Predicting the effects of drugs and unveiling their mechanisms of action using an interpretable pharmacodynamic mechanism knowledge graph (IPM-KG).

Computers in biology and medicine
BACKGROUND: Multiple studies have aimed to consolidate drug-related data and predict drug effects. However, most of these studies have focused on integrating diverse data through correlation rather than representing them based on the pharmacodynamic ...