Geriatrics

Detecting Alzheimer's Disease from Continuous Speech Using Language Models.

BACKGROUND: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from continuous speech by linguistic analysis and modeling. However, few of them utilize language models (LMs) to extract linguistic features and to investigate the lexical-level differences between AD and healthy speech.

[Expectation for AI (Artificial Intelligence) on elderly medical care].

[Expected Role of Artificial Intelligence for Geriatrics].

Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology.

Machine learning (ML) algorithms have found increasing utility in the medical imaging field and numerous applications in the analysis of digital bioma...

Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.

BACKGROUND: Predicting clinical course of cognitive decline can boost clinical trials' power and improve our clinical decision-making. Machine learnin...

Efficacy of end-effector Robot-Assisted Gait Training in subacute stroke patients: Clinical and gait outcomes from a pilot bi-centre study.

BACKGROUND: End-effector robots allow intensive gait training in stroke subjects and promote a successful rehabilitation. A comparison between convent...

Artificial Neural Networks Help to Better Understand the Interplay Between Cognition, Mediterranean Diet, and Physical Performance: Clues from TRELONG Study.

BACKGROUND: Nutrition plays an important role in the aging process. Adherence to the Mediterranean diet (MedDiet) has been shown to be associated with...

Screening for Alzheimer's Disease Using Saliva: A New Approach Based on Machine Learning and Raman Hyperspectroscopy.

BACKGROUND: Alzheimer's disease and related dementias (ADRDs) are being diagnosed at epidemic rates, with incidence to triple from 35 to 115 million c...

Volumetric Histogram-Based Alzheimer's Disease Detection Using Support Vector Machine.

In this research work, machine learning techniques are used to classify magnetic resonance imaging brain scans of people with Alzheimer's disease. Thi...

Alzheimer's Disease Classification Based on Multi-feature Fusion.

BACKGROUND: In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer's Disease ...

Deep Learning for Alzheimer's Disease Classification using Texture Features.

BACKGROUND: We propose a classification method for Alzheimer's disease (AD) based on the texture of the hippocampus, which is the organ that is most a...

Comparative Study of the Effects of Chamomile ( L.) and Cabergoline on Idiopathic Hyperprolactinemia: A Pilot Randomized Controlled Trial.

Chamomile is a fascinating plant quoted in several traditional medicine texts, which has broad-spectrum pharmacological activity and medicinal uses. T...

Cancer Care Treatment Outcome Ontology: A Novel Computable Ontology for Profiling Treatment Outcomes in Patients With Solid Tumors.

PURPOSE: There is as yet no computer-processable resource to describe treatment end points in cancer, hindering our ability to systematically capture ...

Effects of Plant Species, Insecticide, and Exposure Time On the Efficacy Of Barrier Treatments Against .

The effect of 5 plant species (arborvitae [], boxwood [ sp., Japanese honeysuckle [], rhododendron [ sp.], and zebra grass []) and 2 rates of lambda-c...

Hercules: a profile HMM-based hybrid error correction algorithm for long reads.

Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several types of stud...

Deep learning for healthcare: review, opportunities and challenges.

Gaining knowledge and actionable insights from complex, high-dimensional and heterogeneous biomedical data remains a key challenge in transforming hea...

PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging.

Aging biomarkers are the qualitative and quantitative indicators of the aging processes of the human body. Estimation of biological age is important f...

Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis.

AIMS: Diagnosing long QT syndrome (LQTS) is challenging due to a considerable overlap of the QTc-interval between LQTS patients and healthy controls. ...

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and fun...

Exoskeleton and End-Effector Robots for Upper and Lower Limbs Rehabilitation: Narrative Review.

Recovery of upper and lower limbs function is essential to reach independence in daily activities in patients with upper motor neuron syndrome (UMNS)....