Geriatrics

Pervasive Technology-Enabled Care and Support for People with Dementia: The State of Art and Research Issues

Dementia is a mental illness that people live with all across the world. No one is immune. Nothing can predict its onset. The true story of dementia remains unknown globally, partly due to the denial of dementia symptoms and partly due to the social stigma attached to the disease. In recent years, dementia as a mental illness has received a lot of attention from the scientific community and heal...

XBG: End-to-end Imitation Learning for Autonomous Behaviour in Human-Robot Interaction and Collaboration

This paper presents XBG (eXteroceptive Behaviour Generation), a multimodal end-to-end Imitation Learning (IL) system for a whole-body autonomous humanoid robot used in real-world Human-Robot Interaction (HRI) scenarios. The main contribution of this paper is an architecture for learning HRI behaviours using a data-driven approach. Through teleoperation, a diverse dataset is collected, comprising...

ClinicalLab: Aligning Agents for Multi-Departmental Clinical Diagnostics in the Real World

LLMs have achieved significant performance progress in various NLP applications. However, LLMs still struggle to meet the strict requirements for ac...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease

\textbf{Objective:} Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as Mild Cognitiv...

Machine learning in time-lapse imaging to differentiate embryos from young vs old mice†.

Time-lapse microscopy for embryos is a non-invasive technology used to characterize early embryo development. This study employs time-lapse microscopy...

End-to-End Hybrid Refractive-Diffractive Lens Design with Differentiable Ray-Wave Model

Hybrid refractive-diffractive lenses combine the light efficiency of refractive lenses with the information encoding power of diffractive optical el...

Disease-driven domain generalization for neuroimaging-based assessment of Alzheimer's disease.

Development of deep learning models to evaluate structural brain changes caused by cognitive impairment in MRI scans holds significant translational v...

Early Indicators of the Impact of Using AI in Mammography Screening for Breast Cancer.

Background Retrospective studies have suggested that using artificial intelligence (AI) may decrease the workload of radiologists while preserving mam...

Smart Multimodal In-Bed Pose Estimation Framework Incorporating Generative Adversarial Neural Network.

Monitoring in-bed pose estimation based on the Internet of Medical Things (IoMT) and ambient technology has a significant impact on many applications ...

AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning.

Background Visual assessment of amyloid PET scans relies on the availability of radiologist expertise, whereas quantification of amyloid burden typica...

Arrhythmic Mitral Valve Prolapse Phenotype: An Unsupervised Machine Learning Analysis Using a Multicenter Cardiac MRI Registry.

Purpose To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials ...

AI and Chest Radiographs: A Dawning Era in Osteoporosis Screening.

Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial.

Background Diagnosing osteoporosis is challenging due to its often asymptomatic presentation, which highlights the importance of providing screening f...

ADEP: A Novel Approach Based on Discriminator-Enhanced Encoder-Decoder Architecture for Accurate Prediction of Adverse Effects in Polypharmacy

Motivation: Unanticipated drug-drug interactions (DDIs) pose significant risks in polypharmacy, emphasizing the need for predictive methods. Recent ...

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure.

MOTIVATION: Coding and noncoding RNA molecules participate in many important biological processes. Noncoding RNAs fold into well-defined secondary str...

AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.

Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers...

[A study of cognitive impairment quantitative assessment method based on gait characteristics].

Alzheimer's disease (AD) is a common and serious form of elderly dementia, but early detection and treatment of mild cognitive impairment can help slo...

Exploration of Imaging Genetic Biomarkers of Alzheimer's Disease Based on a Machine Learning Method.

BACKGROUND: Alzheimer's disease (AD) is an irreversible primary brain disease with insidious onset. The rise of imaging genetics research has led nume...

Deep Learning-Augmented ECG Analysis for Screening and Genotype Prediction of Congenital Long QT Syndrome.

IMPORTANCE: Congenital long QT syndrome (LQTS) is associated with syncope, ventricular arrhythmias, and sudden death. Half of patients with LQTS have ...

Transplant nephropathology: Wherefrom, wherein, and whereto.

Renal pathology is a relatively recent entry in nephrology. While diseases of the kidney are old, their study began in the 19th century with the repor...