AIMC Topic: Aged

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Resting state EEG reveals no reliable biomarkers of tinnitus laterality.

Scientific reports
This study assessed whether resting-state quantitative EEG (qEEG) can differentiate tinnitus laterality under rigorous multiple-comparison control and nested, cross-validated machine learning (ML). We analyzed 210 pre-specified qEEG features-spectral...

A novel approach hybrid of ensemble learning and 3-D CNN mechanism: early-stage diagnosis of Alzheimer's disease using EEG signals.

Scientific reports
Alzheimer's disease (AD) is a progressive neurological disorder that causes brain cell degeneration and leads to dementia. Early and accurate detection of AD is crucial, as it allows timely treatment before the brain suffers permanent damage. In rece...

Development and validation of a machine learning-based model to predict the risk of hospitalization death in hospitalized patients with AECOPD.

Scientific reports
Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a leading cause of hospitalization and death in COPD patients. Machine learning (ML) approach is powerful but has a "black box" issue with an undirect interpretation of the ML te...

Predicting All-Cause Mortality in Diabetic Patients 2 Years in Advance Using Aggregated EHR Data and Machine Learning.

Journal of medical systems
This study presents a machine learning-driven model predicting all-cause mortality two years in advance using administrative health data focused on diabetic patients. Integrating hospitalization records, emergency department data, demographics, and c...

Explainable machine learning algorithm predicting working memory performance in Parkinson's disease using task-fMRI.

Journal of neurology
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder that affects both motor and cognitive functions, particularly working memory (WM). Machine learning offers an advantage for decoding complex brain activity patterns, but its applica...

Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection.

Heart (British Cardiac Society)
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is often underdiagnosed. Artificial intelligence (AI)-based notification of HCM suspicion on a 12-lead ECG has been proposed to assist patient identification and evaluation. However, there has been no stu...

The exhaled breath pattern as a potential method for biometrics identification.

Scientific reports
Conventional biometric identification methods relying on Personally Identifiable Information (PII) pose significant challenges concerning privacy and security. Volatile organic compounds (VOCs) in exhaled breath are unique to individuals and can serv...

Revolutionizing AMD detection Bi model CNNs and hybrid feature selection for automated grading.

Scientific reports
Age-related macular degeneration (AMD) is a common cause of vision loss in older adults. The automated grading of AMD from fundus images can aid in early detection and treatment. In this research, we propose a comprehensive framework that can enhance...

Predicting one-year overall survival in patients with AITL using machine learning algorithms: a multicenter study.

Scientific reports
Angioimmunoblastic T-cell lymphoma (AITL) is a life-threatening hematological malignancy. For patients with poor prognosis, especially those with expected survival less than 1 year, the benefits from traditional regimens are extremely limited. Theref...

Development of a serum protein biomarker panel for the diagnosis of pancreatic ductal adenocarcinoma using a machine learning approach.

Scientific reports
Early detection of pancreatic ductal adenocarcinoma (PDA) remains a major clinical challenge due to the lack of reliable biomarkers. We developed and validated a machine learning (ML)-based serum protein biomarker panel to enhance PDA diagnosis. Seru...