AIMC Topic: Aged

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Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research
BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas...

Intensity harmonization techniques influence radiomics features and radiomics-based predictions in sarcoma patients.

Scientific reports
Intensity harmonization techniques (IHT) are mandatory to homogenize multicentric MRIs before any quantitative analysis because signal intensities (SI) do not have standardized units. Radiomics combine quantification of tumors' radiological phenotype...

Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation.

The Lancet. Digital health
BACKGROUND: Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics.

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

PLoS computational biology
Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alcohol-related steatohepatitis, which may progress to alcoholic liver fibrosis (ALF) and eventually to...

A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity.

PloS one
Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim was to develop and evaluate a machine learning algorithm to diagnose COVID-19 in the inpatient settin...

The utility of a deep learning-based algorithm for bone scintigraphy in patient with prostate cancer.

Annals of nuclear medicine
OBJECTIVE: Bone scintigraphy has often been used to evaluate bone metastases. Its functionality is evident in detecting bone metastasis in patients with malignant tumor including prostate cancer, as appropriate treatment and prognosis are dependent o...

Classifications of Neurodegenerative Disorders Using a Multiplex Blood Biomarkers-Based Machine Learning Model.

International journal of molecular sciences
Easily accessible biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), and related neurodegenerative disorders are urgently needed in an aging society to assist early-stage diagnoses. In this study, we aim...

Are we ready for artificial intelligence health monitoring in elder care?

BMC geriatrics
BACKGROUND: The world is experiencing a dramatic increase in the aging population, challenging the sustainability of traditional care models that have relied on in-person monitoring. This debate article discusses whether artificial intelligence healt...

Influence of medical domain knowledge on deep learning for Alzheimer's disease prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) is the most common type of dementia that can seriously affect a person's ability to perform daily activities. Estimates indicate that AD may rank third as a cause of death for older people, after hea...