AI Medical Compendium

Artificial intelligence for accurate tumor size assessment and non-invasive adenocarcinoma prediction in small-sized lung cancer.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Mar 6, 2026

INTRODUCTION: Accurate preoperative imaging is essential for improving the treatment of small lung cancers. Precise identification of non-invasive adenocarcinomas is critical for determining the suitability of sublobar resection. Conventional methodo... read more

Artificial intelligence in microscopic hair imaging for scalp disorders: From image acquisition to clinical decisions.

Medical image analysis Mar 6, 2026

Medical imaging plays a central role in modern clinical decision-making by transforming raw image data into actionable diagnostic insights. In the context of scalp and hair disorders, microscopic hair imaging has emerged as a critical tool for non-in... read more

EmbBERT: Attention under 2 MB memory.

Neural networks : the official journal of the International Neural Network Society Mar 6, 2026

Transformer architectures based on the attention mechanism have revolutionized natural language processing (NLP), driving major breakthroughs across virtually every NLP task. However, their substantial memory and computational requirements still hind... read more

Overcoming gastrointestinal mucosal barriers: Mechanistic innovations and technical advances in mucosal targeting strategies for animal oral vaccines.

Veterinary microbiology Mar 6, 2026

Infectious diseases caused by pathogenic microorganisms (such as Escherichia coli, Avian influenza virus (AIV), Rotavirus, etc.) that primarily invade through mucosal surfaces like the digestive tract and respiratory tract not only severely restrict ... read more

FreqConvMamba: Frequency-guided hierarchical hybrid SSM-CNN for medical image segmentation.

Medical image analysis Mar 6, 2026

Accurate segmentation of medical images is a fundamental prerequisite for quantitative disease diagnosis, treatment planning, and computational pathology. Although convolutional neural networks (CNNs) and Mamba-based approaches have shown promise in ... read more

Modeling inter-slice dependencies with temporal graph learning for Alzheimer's disease.

Journal of the neurological sciences Mar 6, 2026

Accurate and early diagnosis of Alzheimer's disease (AD) remains a major clinical challenge, particularly in distinguishing mild cognitive impairment (MCI) from cognitively normal (CN) aging. Conventional approaches that rely solely on pre-trained 2D... read more

Multiple instance learning approach for automated gallbladder cancer detection using ultrasound imaging: multi-center validation of a deep learning model with the public dataset contribution.

The Lancet regional health. Southeast Asia Mar 6, 2026

BACKGROUND: Gallbladder cancer (GBC) diagnosis is challenging due to overlapping imaging features. We developed and validated a multiple instance learning (MIL) model for automated GBC detection using a large-scale multi-center ultrasound dataset and... read more

Machine learning and Regression-Based models for prediction of postoperative atrial fibrillation following coronary artery bypass grafting: A systematic review and meta-analysis.

International journal of cardiology. Cardiovascular risk and prevention Mar 6, 2026

BACKGROUND: Postoperative atrial fibrillation (POAF) is a common complication following coronary artery bypass grafting (CABG) and is associated with adverse clinical outcomes. Traditional risk prediction models show limited accuracy, prompting incre... read more

Evaluating Generative Artificial Intelligence Models' Responses to Questions About Scaphoid Fracture and Scaphoid Nonunion.

Journal of hand surgery global online Mar 6, 2026

PURPOSE: To evaluate and compare the responses of ChatGPT and Google Gemini to common patient questions about scaphoid fracture and scaphoid nonunion, and to compare responses between hand fellowship-trained orthopedic and plastic surgeons. METHODS: ... read more

VISTA-3D : Training-free unfolding for vision-based 3D object detection.