Geriatrics

Machine Learning-Enhanced Hyperspectral Raman Imaging for Label-Free Molecular Atlas of Alzheimer's Brain.

Label-free molecular imaging that enables the construction of a molecular atlas of biological tissues is vital for understanding complex physiological and pathological processes. Conventional bioimaging modalities, including positron-emission tomography (PET), magnetic-resonance imaging (MRI), immunoassays, and fluorescence microscopy, provide valuable structural and functional information but rem...

Deep learning-based cognitive impairment brain imaging analysis: New methods, new technologies, and new paradigms.

Cognitive impairment arising from ischemic stroke, Alzheimer's disease, and Parkinson's disease presents distinct structural and network-level alterations. Brain magnetic resonance imaging offers a non-invasive and high-resolution approach to assess these changes, while deep learning provides powerful tools for automated analysis. Given that accurate lesion delineation, precise localization of abn...

Early Alzheimer's disease classification via structure and feature-based graph attention network from multi-center data.

With the increasing Alzheimer's disease (AD) prevalence, morbidity, and mortality, its early diagnosis is particularly important. The multi-modal data...

Speech Biomarkers From Smartphone Calls Track Progression in REM Sleep Behavior Disorder and Parkinson's Disease.

OBJECTIVE: This 24-month longitudinal study involving isolated rapid eye movement sleep behavior disorder (iRBD), early-stage Parkinson's disease (PD)...

Smiling difficulties in Alzheimer's disease linked to reduced nucleus accumbens and pallidum brain volume: Deep learning insights.

Patients tend to lose the ability to smile during the course of dementia. However, such impairments have rarely been reported, likely due to challenge...

NAD+ restores proteostasis through splicing-dependent autophagy.

Autophagy preserves neuronal integrity by clearing damaged proteins and organelles, but its efficiency declines with aging and neurodegeneration. Depl...

Shadow-DETR: Alleviating matching conflicts through shadow queries.

Leveraging the end-to-end detection capability enabled by one-to-one matching, DETR has achieved state-of-the-art performance in simplified pipelines....

M44TMD: A multimodal, multi-task deep learning framework for comprehensive assessment of TMD-related abnormalities.

OBJECTIVE: Existing deep learning (DL) approaches for assessing temporomandibular disorders (TMD) are limited by underutilization of magnetic resonanc...

Serum FSTL-1 and AI-assessed muscle parameters in cancer-related malnutrition.

OBJECTIVES: Follistatin-like protein-1 (FSTL-1) is emerging as a myokine linking skeletal and muscle biology. We investigated the relationship between...

Recent Advances in Musculoskeletal Radiology: Bridging Innovation and Clinical Application.

Recent advances in musculoskeletal (MSK) radiology have markedly improved diagnostic accuracy through innovations in MRI, CT, and artificial intellige...

Comment on Development and Validation of a Machine Learning-Based Predictive Model for Postoperative Frailty in Patients with Non-Small-Cell Lung Cancer and its Relation to Early Recovery.

Integrated analysis of single-cell and bulk RNA-seq data identifies NR4A1-associated macrophages in immunoglobulin A nephropathy.

Immunoglobulin A nephropathy (IgAN), the most prevalent primary glomerulonephritis worldwide, is characterized by chronic renal inflammation and progr...

Tenuigenin ameliorates Alzheimer's disease by targeting MAP2K1: integrated evidence from network pharmacology and experimental validation.

OBJECTIVE: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder primarily characterized by progressive cognitive impairment and synaptic...

Assessing the Third Wave of Generative AI: Performance of Advanced Models on Text-based Questions From the 2024 Orthopaedic In-training Examination.

INTRODUCTION: Learners are rapidly using generative artificial intelligence (AI) models in their education. We assessed the performance of recently re...

Prediction of postoperative delirium after cardiac surgery by the interplay between preoperative plasma p-tau181 and IL-6 and heart-brain axis related factors: results from the prospective observational study FINDERI.

Postoperative delirium (POD) following cardiac surgery is a severe complication. There is evidence of a link between neuroinflammation and neurodegene...

Deep learning-based micro-CT grayscale analysis for early detection and staging of osteoporosis in rats.

BACKGROUND: Rat models are widely used in preclinical osteoporosis research to study disease mechanisms and evaluate therapies. Current Micro-CT studi...

Complexity of olfactory-evoked EEG as an evidence-based marker of Alzheimer's disease.

Olfactory impairment is an early symptom of Alzheimer's disease (AD). However, currently used olfactory task-based functional magnetic resonance imagi...

State-space models are accurate and efficient neural operators for dynamical systems.

Physics-informed machine learning (PIML) has emerged as a promising alternative to classical methods for predicting dynamical systems, offering faster...

Advances in occult cancer screening for patients with unprovoked venous thromboembolism: A narrative review of epidemiology, risk, and clinical strategies.

BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...

Multi-scale feature enhancement in multi-task learning for medical image analysis.

Traditional deep learning approaches in medical image analysis usually focus on either segmentation or classification, which limits their ability to e...