Exercise & Fitness

Noninvasive detection of diabetes in obstructive sleep apnea based on overnight SpO signal and deep learning.

The prevalence of obstructive sleep apnea comorbid with diabetes is high while the awareness of diabetes is low. There is a strong need for new diagnostic biomarkers to detect diabetes at an early stage. Therefore, we aimed to establish an automatic, deep-learning based model that could be applied to assess diabetes risks using overnight SpO signals. The samples were derived from the Sleep Heart H...

The Diagnosis of Cardiovascular Disease Using Simple Blood Biomarkers Through AI and Big Data.

Cardiovascular disease (CVD) is the leading cause of global mortality, diagnosed primarily through costly imaging modalities which are often overused in asymptomatic patients. Our project aims to develop an AI-based solution for CVD risk stratification using routine blood biomarkers, serving as a pre-imaging test. We used anonymized data from over 500,000 UK Biobank (UKB) patients with CVD assessm...

Dynamic Inverse Reinforcement Learning for Feedback-driven Reward Estimation in Brain Machine Interface Tasks.

Reinforcement learning (RL)-based brain machine interfaces (BMIs) provide a promising solution for paralyzed people. Enhancing the decoding performanc...

MolLM: a unified language model for integrating biomedical text with 2D and 3D molecular representations.

MOTIVATION: The current paradigm of deep learning models for the joint representation of molecules and text primarily relies on 1D or 2D molecular for...

Understanding and predicting pregnancy termination in Bangladesh: A comprehensive analysis using a hybrid machine learning approach.

Reproductive health issues, including unsafe pregnancy termination, remain a significant concern for women in developing nations. This study focused o...

Modified-Improved Fitness Dependent Optimizer for Complex and Engineering Problems

Fitness dependent optimizer (FDO) is considered one of the novel swarm intelligent algorithms. Recently, FDO has been enhanced several times to impr...

Unsupervised Machine Learning in Countermovement Jump and Isometric Mid-Thigh Pull Performance Produces Distinct Combat and Physical Fitness Clusters in Male and Female U.S. Marine Corps Recruits.

INTRODUCTION: Several challenges face the U.S. Marine Corps (USMC) and other services in their efforts to design recruit training to augment warfighte...

SyROCCo: Enhancing Systematic Reviews using Machine Learning

The sheer number of research outputs published every year makes systematic reviewing increasingly time- and resource-intensive. This paper explores ...

The Benefits of Power Regularization in Cooperative Reinforcement Learning

Cooperative Multi-Agent Reinforcement Learning (MARL) algorithms, trained only to optimize task reward, can lead to a concentration of power where t...

Cutting through the noise to motivate people: A comprehensive analysis of COVID-19 social media posts de/motivating vaccination

The COVID-19 pandemic exposed significant weaknesses in the healthcare information system. The overwhelming volume of misinformation on social media...

Fair by design: A sociotechnical approach to justifying the fairness of AI-enabled systems across the lifecycle

Fairness is one of the most commonly identified ethical principles in existing AI guidelines, and the development of fair AI-enabled systems is requ...

Countrywide natural experiment reveals impact of built environment on physical activity

While physical activity is critical to human health, most people do not meet recommended guidelines. More walkable built environments have the poten...

Diversity in Evolutionary Dynamics

We consider the dynamics imposed by natural selection on the populations of two competing, sexually reproducing, haploid species. In this setting, t...

Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis

Cognitive Diagnosis~(CD), which leverages students and exercise data to predict students' proficiency levels on different knowledge concepts, is one...

Participatory Approaches in AI Development and Governance: A Principled Approach

The widespread adoption of Artificial Intelligence (AI) technologies in the public and private sectors has resulted in them significantly impacting ...

Neural Architecture Search Using Covariance Matrix Adaptation Evolution Strategy.

Evolution-based neural architecture search methods have shown promising results, but they require high computational resources because these methods i...

OLB-AC: toward optimizing ligand bioactivities through deep graph learning and activity cliffs.

MOTIVATION: Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the ...

Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.

This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected artificial intelligence (AI)-based large language mo...

DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm.

MOTIVATION: Despite the extensive manufacturing of antiviral drugs and vaccination, viral infections continue to be a major human ailment. Antiviral p...

Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape.

MOTIVATION: Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and prot...