Geriatrics

Artificial intelligence and the aging mind.

Investigating the robustness of a deep learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions.

Quantitative phase retrieval (QPR) in propagation-based x-ray phase contrast imaging of heterogeneou...

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries.

Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress ...

Comment on 'study and validation of an explainable machine learning-based mortality prediction following emergency surgery in the elderly: a prospective observational study'.

Age-specific biomechanical challenges and engagement in dynamic balance training with robotic or virtual real-time visual feedback.

Challenging balance training that targets age-related neuromuscular and motor coordination deficits ...

An explainable artificial intelligence approach to spatial navigation based on hippocampal circuitry.

Learning to navigate a complex environment is not a difficult task for a mammal. For example, findin...

Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: Algorithms and dataset.

For automatic EEG diagnosis, this paper presents a new EEG data set with well-organized clinical ann...

Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows.

Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance...

Artificial Intelligence Technologies in the Microsurgical Operating Room (Review).

Surgery performed by a novice neurosurgeon under constant supervision of a senior surgeon with the e...

X-CHAR: A Concept-based Explainable Complex Human Activity Recognition Model.

End-to-end deep learning models are increasingly applied to safety-critical human activity recogniti...

An End-to-End Natural Language Processing System for Automatically Extracting Radiation Therapy Events From Clinical Texts.

PURPOSE: Real-world evidence for radiation therapy (RT) is limited because it is often documented on...

Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples.

BACKGROUND: Dementia's diagnostic protocols are mostly based on standardised neuroimaging data colle...

Natural language processing techniques for studying language in pathological ageing: A scoping review.

BACKGROUND: In the past few years there has been a growing interest in the employment of verbal prod...

Automatic implant shape design for minimally invasive repair of pectus excavatum using deep learning and shape registration.

Minimally invasive repair of pectus excavatum (MIRPE) is an effective method for correcting pectus e...

Anti-inflammatory therapy enables robot-actuated regeneration of aged muscle.

Robot-actuated mechanical loading (ML)-based therapies ("mechanotherapies") can promote regeneration...

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful ...

AMLnet, A deep-learning pipeline for the differential diagnosis of acute myeloid leukemia from bone marrow smears.

Acute myeloid leukemia (AML) is a deadly hematological malignancy. Cellular morphology detection of ...

Learning end-to-end patient representations through self-supervised covariate balancing for causal treatment effect estimation.

A causal effect can be defined as a comparison of outcomes that result from two or more alternative ...

Influence of artificial intelligence in education on adolescents' social adaptability: The mediatory role of social support.

Artificial intelligence (AI) is widely used in the field of education at present, but people know li...

HGM-cNet: Integrating hippocampal gray matter probability map into a cascaded deep learning framework improves hippocampus segmentation.

A robust cascaded deep learning framework with integrated hippocampal gray matter (HGM) probability ...

Agricultural Robot-Centered Recognition of Early-Developmental Pest Stage Based on Deep Learning: A Case Study on Fall Armyworm ().

Accurately detecting early developmental stages of insect pests (larvae) from off-the-shelf stereo c...