Geriatrics

[Application of Deep Learning in Differential Diagnosis of Ameloblastoma and Odontogenic Keratocyst Based on Panoramic Radiographs].

Objective To evaluate the accuracy of different convolutional neural networks (CNN),representative deep learning models,in the differential diagnosis of ameloblastoma and odontogenic keratocyst,and subsequently compare the diagnosis results between models and oral radiologists. Methods A total of 1000 digital panoramic radiographs were retrospectively collected from the patients with ameloblastoma...

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.

Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient ...

AgeAnno: a knowledgebase of single-cell annotation of aging in human.

Aging is a complex process that accompanied by molecular and cellular alterations. The identification of tissue-/cell type-specific biomarkers of agin...

Voxel-based morphometry and a deep learning model for the diagnosis of early Alzheimer's disease based on cerebral gray matter changes.

This study aimed to analyse cerebral grey matter changes in mild cognitive impairment (MCI) using voxel-based morphometry and to diagnose early Alzhei...

Biomarkers of aging - current state of knowledge.

Aging is a process of gradual decline in the functional capacity of the human body that leads to a significant increase in the risk of death over time...

Exploring Anti-osteoporosis Medicinal Herbs using Cheminformatics and Deep Learning Approaches.

BACKGROUND: Osteoporosis is a prevalent disease for the aged population. Chinese herbderived natural compounds have anti-osteoporosis effects. Due to ...

An end-to-end multi-task system of automatic lesion detection and anatomical localization in whole-body bone scintigraphy by deep learning.

SUMMARY: Limited by spatial resolution and visual contrast, bone scintigraphy interpretation is susceptible to subjective factors, which considerably ...

[Frailty and surgical tolerability in elderly patients undergoing robot-assisted radical cystectomy (RARC)].

Robot-assisted radical cystectomy (RARC) has become a gold standard therapeutic option for muscle-invasive bladder cancer and selected cases with T1 b...

Usability and Acceptability of Social Robot Pets Among Community-Dwelling Veterans Living With Dementia and Their Caregivers.

Social robot pets promote engagement and psychosocial well-being among older adults, yet little is known about their use among community-dwelling Vete...

[Effect of EIT-guided individualized PEEP setting on the incidence of hypoxemia in elderly patients undergoing robot-assisted radical prostatectomy].

To investigate the effect of individualized positive end expiratory pressure (PEEP) setting guided by chest electrical impedance tomography (EIT) on ...

Development and validation of a deep learning algorithm based on fundus photographs for estimating the CAIDE dementia risk score.

BACKGROUND: the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) dementia risk score is a recognised tool for dementia risk strat...

Feasibility of robot-assisted radical prostatectomy in men at senior age ≥75 years: perioperative, functional, and oncological outcomes of a high-volume center.

OBJECTIVES: The aim of this study was to assess whether age ≥75 years impairs surgical, functional, and oncological outcomes after robot-assisted radi...

Influence of nurses in the implementation of artificial intelligence in health care: a scoping review.

Objective This scoping review maps the approach undertaken by nurses to influence the implementation of artificial intelligence in health care. It als...

Towards emotionally aligned social robots for dementia: perspectives of care partners and persons with dementia.

BACKGROUND: Persons living with dementia and their care partners place a high value on aging in place and maintaining independence. Socially assistive...

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease.

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Al...

Deep learning radiomics under multimodality explore association between muscle/fat and metastasis and survival in breast cancer patients.

Sarcopenia is correlated with poor clinical outcomes in breast cancer (BC) patients. However, there is no precise quantitative study on the correlatio...

Multimodal attention-based deep learning for Alzheimer's disease diagnosis.

OBJECTIVE: Alzheimer's disease (AD) is the most common neurodegenerative disorder with one of the most complex pathogeneses, making effective and clin...

Dynamic single-photon 3D imaging with a sparsity-based neural network.

Deep learning is emerging as an important tool for single-photon light detection and ranging (LiDAR) with high photon efficiency and image reconstruct...

[Comparison of the predictive performance of Logistic regression, BP neural network and support vector machine model for the risk of acute exacerbation of readmission in elderly patients with chronic obstructive pulmonary disease within 30 days].

OBJECTIVE: To compare the effectiveness of Logistic regression, BP neural network and support vector machine models in the prediction of 30-day risk o...

An ISB-consistent Denavit-Hartenberg model of the human upper limb for joint kinematics optimization: validation on synthetic and robot data during a typical rehabilitation gesture.

Several biomedical contexts such as diagnosis, rehabilitation, and ergonomics require an accurate estimate of human upper limbs kinematics. Wearable i...