AIMC Topic: Aged

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Detecting IDH and TERTp mutations in diffuse gliomas using H-MRS with attention deep-shallow networks.

Computers in biology and medicine
BACKGROUND: Preoperative and noninvasive detection of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutations in glioma is critical for prognosis and treatment planning. This study aims to develop deep lear...

Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.

Computers in biology and medicine
An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three l...

Significance of gender, brain region and EEG band complexity analysis for Parkinson's disease classification using recurrence plots and machine learning algorithms.

Physical and engineering sciences in medicine
Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating dopamine in the SN per compacta. Electroencephalogram (EEG) plays an important role in diagnosing PD as it offers a non-invasive continuous assessment ...

Development and Validation of Machine Learning-Based Model for Hospital Length of Stay in Patients Undergoing Endovascular Interventional Embolization for Intracranial Aneurysms.

World neurosurgery
OBJECTIVE: This study was to explore the factors associated with prolonged hospital length of stay (LOS) in patients with intracranial aneurysms (IAs) undergoing endovascular interventional embolization and construct prediction model machine learning...

Optimizing stroke prediction using gated recurrent unit and feature selection in Sub-Saharan Africa.

Clinical neurology and neurosurgery
BACKGROUND: Stroke remains a leading cause of death and disability worldwide, with African populations bearing a disproportionately high burden due to limited healthcare infrastructure. Early prediction and intervention are critical to reducing strok...

Natural language processing-based classification of early Alzheimer's disease from connected speech.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: The automated analysis of connected speech using natural language processing (NLP) emerges as a possible biomarker for Alzheimer's disease (AD). However, it remains unclear which types of connected speech are most sensitive and specific...

An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.

Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thick...

Deep learning-based algorithm for classifying high-resolution computed tomography features in coal workers' pneumoconiosis.

Biomedical engineering online
BACKGROUND: Coal workers' pneumoconiosis is a chronic occupational lung disease with considerable pulmonary complications, including irreversible lung diseases that are too complex to accurately identify via chest X-rays. The classification of clinic...

Artificial intelligence-assisted platform performs high detection ability of hepatocellular carcinoma in CT images: an external clinical validation study.

BMC cancer
BACKGROUND: Accurate detection of hepatocellular carcinoma (HCC) in multiphasic contrast CT is essential for effective treatment and surgical planning. However, the variety of CT images, the misdiagnosis and missed diagnosis, and the inconsistent dia...