AIMC Topic: Humans

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Serum metabolic patterns reveal the diagnostic and prognostic role of alanine abnormality in ocular adnexal lymphoma.

Proceedings of the National Academy of Sciences of the United States of America
Ocular adnexal lymphoma (OAL) is the most common orbital malignancy in adults. Advanced tools for precise diagnosis and prognosis of OAL are in demand. Here, the nanoparticle-enhanced laser desorption/ionization mass spectrometry was applied for the ...

Enhanced stroke risk prediction in hypertensive patients through deep learning integration of imaging and clinical data.

BMC medical informatics and decision making
BACKGROUND: Stroke is one of the leading causes of death and disability worldwide, with a significantly elevated incidence among individuals with hypertension. Conventional risk assessment methods primarily rely on a limited set of clinical parameter...

Multimodal deep learning for allergenic proteins prediction.

BMC biology
BACKGROUND: Accurate prediction of allergens is essential for identifying the sources of allergic reactions and preventing future exposure to harmful triggers; however, the limited performance of current prediction tools hinders their practical appli...

Thyroid disease classification using generative adversarial networks and Kolmogorov-Arnold network for three-class classification.

BMC medical informatics and decision making
Thyroid disease classification is a critical challenge in medical diagnostics, requiring accurate differentiation between hyperthyroidism, hypothyroidism, and normal thyroid function. This study introduces an advanced machine learning approach that i...

TA-SSM net: tri-directional attention and structured state-space model for enhanced MRI-Based diagnosis of Alzheimer's disease and mild cognitive impairment.

BMC medical imaging
Early diagnosis of Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI), is critical for effective prevention and treatment. Computer-aided diagnosis using magnetic resonance imaging (MRI) provides a cost-effective and objectiv...

Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis.

BMC anesthesiology
BACKGROUND: Intraoperative hypotension (IOH), defined as a mean arterial pressure (MAP) below 65 mmHg, is a common complication during surgery and is associated with significant postoperative morbidity, including acute kidney injury, myocardial injur...

Using a large language model (ChatGPT) to assess risk of bias in randomized controlled trials of medical interventions: protocol for a pilot study of interrater agreement with human reviewers.

BMC medical research methodology
BACKGROUND: Risk of bias (RoB) assessment is an essential part of systematic reviews that requires reading and understanding each eligible trial and RoB tools. RoB assessment is subject to human error and is time-consuming. Machine learning-based too...

Identification and validation of an explainable machine learning model for vascular depression diagnosis in the older adults: a multicenter cohort study.

BMC medicine
BACKGROUND: Vascular depression (VaDep) is a prevalent affective disorder in older adults that significantly impacts functional status and quality of life. Early identification and intervention are crucial but largely insufficient in clinical practic...

Advanced multi-label brain hemorrhage segmentation using an attention-based residual U-Net model.

BMC medical informatics and decision making
OBJECTIVE: This study aimed to develop and assess an advanced Attention-Based Residual U-Net (ResUNet) model for accurately segmenting different types of brain hemorrhages from CT images. The goal was to overcome the limitations of manual segmentatio...