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Comprehensive integration of single-cell and bulk transcriptome to reveal plasma cell heterogeneity and a prognosis signature in head and neck squamous cell carcinoma.

Oral oncology
Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a low five-year survival rate, emphasising the urgent need for effective prognostic biomarkers to guide patient stratification and personalised treatment. Plasma cells (PCs)...

Predicting fracture toughness of human cortical bone from donors with and without type 2 diabetes using Raman spectroscopy and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Type 2 diabetes mellitus (T2DM) is associated with increased skeletal fragility, yet standard clinical assessments often fail to detect diabetes-induced changes in bone quality. Raman spectroscopy (RS), a label-free and non-destructive technique, off...

Generative Artificial Intelligence (AI) to Uncover Insights From Breast Cancer Patients' Perceptions to Mindfulness-Based Stress Reduction (MBSR) Interventions.

Holistic nursing practice
The study's central objective is to harness the power of generative Artificial Intelligence (AI), in particular based on Large Language Models, as a valuable resource for delving deeper into the insights offered by patients with breast cancer (BC) wh...

Screening, Validation, and Machine Learning-Based Evaluation of Serum Protein Biomarkers for Esophageal Squamous Cell Carcinoma Based on Single-Cell Subtype-Specific Genes.

Journal of proteome research
Cellular heterogeneity of epithelial cells and fibroblasts is critical in esophageal squamous cell carcinoma development (ESCC). Identifying dysregulated subtype-specific genes in these cells is essential for early diagnosis and treatment. In this st...

Robotic arm vs. stereotactic frame in deep brain stimulation surgery for movement disorders: a retrospective cohort study.

Acta neurochirurgica
BACKGROUND: Recently, robotic arms have been incorporated into the implantation of electrodes for deep brain stimulation (DBS).This study aimed to determine the accuracy of brain electrode placement, initial clinical efficacy, and safety profile of t...

MRI-derived quantification of hepatic vessel-to-volume ratios in chronic liver disease using a deep learning approach.

European radiology experimental
BACKGROUND: We aimed to quantify hepatic vessel volumes across chronic liver disease stages and healthy controls using deep learning-based magnetic resonance imaging (MRI) analysis, and assess correlations with biomarkers for liver (dys)function and ...

Exploring GPT-4o's multimodal reasoning capabilities with panoramic radiograph: the role of prompt engineering.

Clinical oral investigations
OBJECTIVES: The aim of this study was to evaluate GPT-4o's multimodal reasoning ability to review panoramic radiograph (PR) and verify its radiologic findings, while exploring the role of prompt engineering in enhancing its performance.

Domain Knowledge Inclusive Monotonic Neural Network Guides Patient-Specific Induction of General Anesthesia Dosing.

A&A practice
BACKGROUND: Postinduction hypotension is a well-known risk factor for adverse postoperative outcomes. Anesthesiologists estimate anesthetic dosages based on a patient's chart and domain knowledge. Machine learning is increasingly applied in predictin...