AIMC Topic: Algorithms

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DGMM: A Deep Learning-Genetic Algorithm Framework for Efficient Lead Optimization in Drug Discovery.

Journal of chemical information and modeling
Lead optimization in drug discovery faces the dual challenge of maintaining structural diversity while preserving core molecular features and optimizing the balance between biological activity and drug-like properties. To address these challenges, we...

From Function to Implementation: Exploring Degeneracy in Evolved Artificial Agents.

Neural computation
Degeneracy-the ability of different structures to perform the same function-is a fundamental feature of biological systems, contributing to their robustness and evolvability. However, the ubiquity of degeneracy in systems generated through adaptive p...

Algorithmic Fairness in Machine Learning Prediction of Autism Using Electronic Health Records.

Studies in health technology and informatics
Efforts to improve early diagnosis of autism spectrum disorder (ASD) in children are beginning to use machine learning (ML) approaches applied to real-world clinical datasets, such as electronic health records (EHRs). However, sex-based disparities i...

Comparing Deterministic and Stochastic Reinforcement Learning for Glucose Regulation in Type 1 Diabetes.

Studies in health technology and informatics
Type 1 Diabetes (T1D) is a chronic condition affecting millions worldwide, requiring external insulin administration to regulate blood glucose levels and prevent serious complications. Artificial Pancreas Systems (APS) for managing T1D currently rely...

Development and Validation of Machine-Learning Algorithms to Predict the Onset of Depression Using Electronic Health Record Data: A Prognostic Modeling Study.

Studies in health technology and informatics
INTRODUCTION: Early detection and intervention are crucial for reducing the impacts of depression and associated healthcare costs. Few studies have used electronic health records (EHR) and machine learning (ML) with a longitudinal design to predict d...

Automate Creating, Customizing, and Optimizing Comorbidity Indices Using a Data-Driven AI/ML Approach.

Studies in health technology and informatics
Due to individual differences in severity of illness, clinical studies typically use a comorbidity index to adjust outcomes. With the increasing use of electronic health records (EHRs) to assess the quality of care, a key question arises: how to adju...

A Scoping Review of AI/ML Algorithm Updating Practices for Model Continuity and Patient Safety Using a Simplified Checklist.

Studies in health technology and informatics
The ubiquity of clinical artificial intelligence (AI) and machine learning (ML) models necessitates measures to ensure the reliability of model output over time. Previous reviews have highlighted the lack of external validation for most clinical mode...

An Ensemble Approach Integrating Retrieval-Augmented Large Language Models and Boosting Algorithms for Enhanced Catatonia Phenotyping.

Studies in health technology and informatics
A critical first step in using large-scale data to study catatonia is the development of precise phenotyping algorithms that can identify instances of the condition. In this work, we present an ensemble approach that combines retrieval-augmented gene...

Precise classification of traditional Chinese medicine sources using intelligent fusion of hyperspectral imaging-mass spectrometry data combined with machine learning: A case study of American ginseng.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The application of artificial intelligence in traditional Chinese medicine (TCM) has become a hot topic in the scientific community. American ginseng (AG), a perennial herb with a rich history, is widely utilized in clinical settings due to its diver...

The Hidden Crux of Correctly Determining Octanol-Water Partition Coefficients.

Molecular pharmaceutics
The partitioning of molecules between an aqueous and an organic medium is of major interest for pharmaceutical development and the chemical industry. It characterizes the impact of substances to the environment and to humans, e.g., their accumulation...