Dermatology

Context-Guided Mixture-of-Experts with Multimodal LLMs for Lesion Detection in Buccal Mucosa Images.

INTRODUCTION AND AIMS: Oral lesions are highly prevalent globally, and oral cancer ranks among the most common malignancies, underscoring the need for AI-driven tools to support early detection and triage, especially in resource-scarce settings. This work investigates the capabilities of multimodal large language models (MLLMs) for automated detection of oral lesions in smartphone-acquired buccal ...

Updates on tuberculosis imaging.

Tuberculosis (TB) remains a leading infectious cause of morbidity and mortality worldwide, and major diagnostic and therapeutic challenges persist despite advances in microbiologic and molecular testing. Over the past decade, molecular imaging, especially with FDG PET/CT, has transformed our understanding of TB pathogenesis, the spectrum of early and subclinical disease, mechanisms of disseminatio...

Future cardiovascular events prediction from invasive coronary angiography: A graph representation learning perspective.

Improving risk stratification for coronary artery disease (CAD), the leading global cause of death, remains a daily challenge in clinical practice. Th...

Accurate density functional theory for noncovalent interactions in charged systems.

Accurately modeling noncovalent interactions (NCIs) involving charged systems remains an outstanding challenge in density functional theory (DFT), wit...

The ISLES'24 Dataset: A Multimodal Stroke Imaging Dataset with Hyperacute CT, Acute Postinterventional MRI, and 3-month Clinical Outcomes.

Stroke remains a major global health burden (1,2), although outcomes have improved substantially through imaging-guided therapy and endovascular reper...

Deep-learning computer-aided detection and classification of prostate lesions on biparametric MRI: comparison with expert readers.

OBJECTIVE: To assess the performance of a deep learning-based computer-aided detection (DL-CAD) algorithm for prostate lesion detection and classifica...

Deep Learning and Experimental Validation of BRCA1-Associated Protein-1 Missense Variant Pathogenicity in Uveal Melanoma.

OBJECTIVE: To benchmark the pathogenicity predictions of AlphaMissense, a deep learning model, against high-throughput functional scores from saturati...

High-resolution deep learning DIXON MRI of the sacroiliac joints is non-inferior to standard MRI in patients with suspected axial Spondyloarthritis.

OBJECTIVE: To compare the standard multi-sequence MRI protocol (sMRI) of the sacroiliac joints with a single high-resolution deep learning-reconstruct...

Mucinous vs. non-mucinous pancreatic cysts: diagnostic keys on CT and MRI.

The prevalence of incidentally detected pancreatic cystic lesions has increased substantially with the widespread use of high-resolution CT and MRI. D...

Multi-class classification of autoimmune skin disease by efficient localization of overlapped lesion boundaries using SAM.

BACKGROUND: Detection of Autoimmune skin disease is found challenging due to overlapping features and irregular skin lesion boundaries. Although numer...

Isolated Nausea and Pretibial Rash in a Returning Traveler: Forme Fruste of Leptospirosis.

Leptospirosis is difficult to diagnose because of protean nonspecific clinical manifestations and the lack of rapid, actionable laboratory testing. A ...

Semi-supervised Learning with Online Knowledge Distillation for Skin Lesion Classification.

Deep learning has emerged as a promising approach for skin lesion analysis. However, existing methods mostly rely on fully supervised learning, requir...

Automated detection of basement-membrane breaches in oral squamous cell carcinoma : A comparative study of convolutional neural network architectures.

BACKGROUND: Oral squamous cell carcinoma (OSCC) remains a leading cause of cancer-related morbidity and mortality worldwide. The ability to detect ear...

Artificial Intelligence-assisted Periapical Radiographic Assessment: Lesion Detection, Endodontic Complication Analysis, and Review of Clinical Treatment Recommendations.

INTRODUCTION: Artificial intelligence (AI) systems are increasingly used in dental radiology to support endodontic diagnosis. However, their diagnosti...

Interpretable predictions from whole-body FDG-PET/CT using parameters associated with clinical outcome.

BACKGROUND: Accurate prediction of clinical outcomes is challenging yet important for patient care. The aim of the study was to evaluate a deep learni...

AI-Driven Multi-parametric MS Lesion Analysis from T2-FLAIR Imaging: a Clinical Decision Support Framework for Neuroradiology.

Artificial intelligence (AI) is transforming neuroradiological practice, yet multiple sclerosis (MS) diagnosis remains challenged by qualitative MRI a...

Evolving role of biomarkers in spinal cord injury: From research to clinical translation.

Spinal cord injury (SCI) triggers a complex cascade of cellular and molecular events at the lesion site, driving progressive degeneration of the spina...

Machine learning models for predicting microvascular invasion in hepatocellular carcinoma with three-dimensional whole-lesion 18F-FDG PET radiomics.

OBJECTIVE: To estimate the performance of machine learning models based on preoperative three-dimensional whole-lesion radiomics features for predicti...

Mammography-based artificial intelligence model for predicting axillary lymph node status after neoadjuvant therapy in breast cancer.

OBJECTIVES: Our objective is to develop a deep learning-based artificial intelligence (AI) model capable of analyzing digital mammography (DM) images ...

Imaging-based machine learning for the diagnosis and prognosis of uveal melanoma: a systematic review and meta analysis.