Geriatrics

Optimizing Two-Way Partial AUC With an End-to-End Framework.

The Area Under the ROC Curve (AUC) is a crucial metric for machine learning, which evaluates the ave...

Classification and deep-learning-based prediction of Alzheimer disease subtypes by using genomic data.

Late-onset Alzheimer's disease (LOAD) is the most common multifactorial neurodegenerative disease am...

Acceptance of social assistant robots for the older adults living in the community in China.

BACKGROUND: Social assistant robots (SARs) are an important part of providing high quality health an...

Implementation of a structured robotic colorectal curriculum for general surgery residents.

There is increasing demand for colorectal robotic training for general surgery residents. We impleme...

Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue.

While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP),...

Editorial: Can artificial intelligence help us overcome challenges in geriatrics?

Gigapixel end-to-end training using streaming and attention.

Current hardware limitations make it impossible to train convolutional neural networks on gigapixel ...

Development of a model for the prediction of biological age.

BACKGROUND AND OBJECTIVE: Rates of aging vary markedly among individuals, and biological age serves ...

Evolving a Pipeline Approach for Abstract Meaning Representation Parsing Towards Dynamic Neural Networks.

Meaning Representation parsing aims to represent a sentence as a structured, Directed, Acyclic Graph...

Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery.

Aging is a complex and multifactorial process that increases the risk of various age-related disease...

Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. T...

Machine learning algorithms for identifying predictive variables of mortality risk following dementia diagnosis: a longitudinal cohort study.

Machine learning (ML) could have advantages over traditional statistical models in identifying risk ...

An end-to-end convolutional neural network for automated failure localisation and characterisation of 3D interconnects.

The advancement in the field of 3D integration circuit technology leads to new challenges for qualit...

Comparing end-effector position and joint angle feedback for online robotic limb tracking.

Somatosensation greatly increases the ability to control our natural body. This suggests that supple...

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one...

Lite-SeqCNN: A Light-Weight Deep CNN Architecture for Protein Function Prediction.

The short-and-long range interactions amongst amino-acids in a protein sequence are primarily respon...

Comparison of four machine learning algorithms for a pre-impact fall detection system.

In recent years, real-time health monitoring using wearable sensors has been an active area of resea...

An end-to-end deep learning method for protein side-chain packing and inverse folding.

Protein side-chain packing (PSCP), the task of determining amino acid side-chain conformations given...

Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time.

With an aging population and increased chronic diseases, remote health monitoring has become critica...

Differential diagnosis of benign and malignant vertebral compression fractures: Comparison and correlation of radiomics and deep learning frameworks based on spinal CT and clinical characteristics.

PURPOSE: Differentiating benign from malignant vertebral compression fractures (VCFs) is a diagnosti...

Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence.

Artificial-intelligence (AI) allows large-scale analyses of long-leg-radiographs (LLRs). We used thi...