Dermatology

Imaging of Small Cell Lung Cancer: An Updated Overview of Current and Emerging Applications.

Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite recent therapeutic advances, including immune checkpoint inhibitors and emerging targeted agents, survival outcomes remain poor. Recent molecular insights have identified four transcription factor-driven subtypes-SCLC-A, SCLC-N, SCLC-P, and the inflamed...

Deep Learning-based Automated Coronary Plaque Quantification: First Demonstration With Ultra-high Resolution Photon-counting Detector CT at Different Temporal Resolutions.

OBJECTIVES: The aim of this study was to evaluate the feasibility and reproducibility of a novel deep learning (DL)-based coronary plaque quantification tool with automatic case preparation in patients undergoing ultra-high resolution (UHR) photon-counting detector CT coronary angiography (CCTA), and to assess the influence of temporal resolution on plaque quantification. MATERIALS AND METHODS: In...

Integration Analysis of Bayesian and Machine Learning for Heterogeneity, Biomarkers, and Optimal Combination Regimens of Pucotenlimab in Solid Tumors.

The efficacy of PD-1 inhibitor pucotenlimab (HX008) in solid tumors exhibits heterogeneity. This study integrated data from 6 clinical trials (coverin...

Cross-attention multimodal fusion for EGFR mutation prediction: A predictive model using CT and whole-slide images.

BACKGROUND: The prediction of Epidermal Growth Factor Receptor (EGFR) mutation status in advanced lung adenocarcinoma is crucial for targeted therapy....

Current and Emerging Therapies Targeting the IL-23/IL-17 Axis in Psoriasis.

Over the past two decades, experimental and clinical evidence has established the interleukin-23 (IL-23)/interleukin-17 (IL-17) axis as a key mediator...

Evaluating the interpretation of neck CT/MRI scans by ChatGPT-4V for detecting primary oropharyngeal squamous cell carcinoma: An exploratory study.

OBJECTIVES: Early and accurate detection of head and neck squamous cell carcinoma and the subset of oropharyngeal squamous cell carcinoma (OPSCC) is e...

Radiomics-based outcome prediction for irinotecan-TACE in colorectal liver metastases: advanced analysis from the prospective CIREL trial.

OBJECTIVES: Transarterial chemoembolization (TACE) is a promising locoregional therapy for unresectable colorectal liver metastases, but patient selec...

Automated identification of incidentalomas requiring follow-up: A multi-anatomy evaluation of LLM-based and supervised approaches.

OBJECTIVE: To evaluate large language models (LLMs) against supervised baselines for fine-grained, lesion-level detection of incidentalomas requiring ...

Genetic Predictors of Progression and Skin Rash in Japanese mCSPC Patients Treated With Apalutamide: CUARTET Study.

Despite promising evidence of the efficacy of the androgen deprivation therapy (ADT) plus apalutamide in metastatic castration-sensitive prostate canc...

Quantifying the Heterogeneity of TRUS-Visible Lesions for Predicting Prostate Cancer: A Multicenter Preliminary Study.

RATIONALE AND OBJECTIVES: This study aimed to quantitatively characterize the heterogeneity of Transrectal ultrasound (TRUS)-visible lesions using sub...

Counterfactual Reasoning for Mammogram Classification via Semantic Texture Masking.

Artificial intelligence-based computer-aided diagnosis (CADx) systems have seen growing adoption in mammography, yet the limited interpretability of t...

GR2ST: Spatial Transcriptomics Prediction based on Graph-Enhanced Multimodal Contrastive Learning.

MOTIVATION: Spatial transcriptomics techniques capture gene expression data and spatial coordinates, while simultaneously correlating them with tissue...

GiTNet: A graph-based trajectory-informed network for gaze-supervised medical image segmentation.

Creating fully annotated labels for medical image segmentation is both time-consuming and costly, underscoring the need for efficient annotation schem...

Evaluating the Utility and Limitations of Machine Learning Tumor Segmentation for Automated Longitudinal RANO Treatment Response Classification.

PURPOSE: Machine learning segmentation has emerged in tumor assessment with high performance in volumetric evaluation of brain tumors. It is unclear, ...

Generalizable spinal cord multiple sclerosis lesion segmentation across MRI contrasts, protocols, and centers.

BACKGROUND/OBJECTIVES: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluati...

Vitiligo state assessment based on progressive transfer learning and multimodal domain adaptation.

Vitiligo is a common skin depigmentation disorder; assessing its state is crucial for the treatment outcome. Collecting multimodal data for vitiligo a...

From local textures to global attention: a hybrid feature fusion network for skin lesion classification.

Accurate detection of skin cancer detection using RGB images remains a challenge due to multiple factors including variability in lesion appearance, d...

Machine learning based on magnetic resonance imaging-derived texture features for differentiation of minor salivary gland tumors.

OBJECTIVE: We aimed to differentiate between benign and malignant minor salivary gland tumors using machine learning (ML) based on magnetic resonance ...

Three-dimensional oxygen maps of tumors in real time - Analysis in the context of active tumor vasculature.

BACKGROUND AND OBJECTIVE: Characterizing the tumor microenvironment (TME) requires integrating multiple physiological features, including oxygenation,...

Choline kinase beta promotes psoriasis pathogenesis by regulating sphingolipid metabolism and activating the PI3K/Akt/GSK3β signaling pathway.

Psoriasis is a chronic inflammatory skin disorder characterized by dysregulated lipid metabolism, yet the key molecular drivers remain unclear. This s...