Dermatology

Utilizing data mining to improve asthma control in children: a study on influential factors.

OBJECTIVE: To identify the most influential features of asthma control in children and to assess whe...

GloW-VSNet: A scribble-based weakly supervised framework for global-view vitiligo lesion segmentation.

Vitiligo lesion identification is essential for quantifying disease severity, monitoring disease pro...

Artificial Intelligence in Acne Diagnosis and Management: Current Applications and Future Directions.

Interobserver variability in histopathologic diagnosis of melanocytic neoplasms.

BACKGROUND: Precise histopathologic diagnosis of melanocytic neoplasms is required to guide appropri...

Exploring shared diagnostic genes and molecular mechanisms in multiple sclerosis and psoriasis through bioinformatics analysis and machine learning.

BACKGROUND: Multiple sclerosis (MS) and psoriasis are both immune-mediated inflammatory diseases. Pr...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vascula...

Interpreting Deep Learning-Based Prediction of the BRAF V600E Mutation Using Diagnostic Whole Slide Images in Skin Cutaneous Melanoma.

Deep learning (DL) models have shown promise in predicting molecular alterations directly from hemat...

Super-resolution deep learning reconstruction improves brain MRI quality and detection of metastases.

PURPOSE: Accurate identification of brain metastases is critical for determining prognosis and guidi...

Machine learning models for CT-based classification of ischemic stroke onset time within or beyond 4.5 h: a comparison of approaches.

OBJECTIVES: To compare machine learning models using different combinations of clinical and imaging ...

ChatGPT-4o as a diagnostic tool for skin cancer: Diagnostic accuracy in melanoma and non-melanoma detection.

INTRODUCTION: The global incidence of skin cancer is rising, emphasizing the need for early detectio...

A comparative study of computer vision models for oral cancer detection from oral photographs.

BACKGROUND AND OBJECTIVE: Early detection of oral cavity cancers is critical for improving patient s...

Morphologic Evaluation of Hyperchromatic Crowded Groups Present in Cervical Thin Prep Cytology Tests as Identified by the Hologic Genius Digital Diagnostics System: A Descriptive Study.

BACKGROUND: Our descriptive study focused on morphologic characteristics of hyperchromatic crowded g...

Precision treatment with artificial intelligence assisted subtyping enhances therapeutic efficacy in HR+/HER2- breast cancer: The LINUXtrial.

We report the results of LINUX (NCT05594095), a multicenter, randomized, controlled phase II platfor...

Artificial intelligence in the detection of multiple sclerosis plaques: Can it influence the treatment decision?

BACKGROUND AND PURPOSE: To monitor multiple sclerosis (MS) progression, follow-up MRIs are used to d...

Machine learning models for predicting response to epidermal growth factor receptor tyrosine kinase inhibitors in non-small cell lung cancer brain metastases: a systematic review and meta-analysis.

BACKGROUND: Predicting clinical and radiological outcomes of epidermal growth factor receptor tyrosi...

Machine learning-guided composite ionic liquid-based system for dual-drug delivery targeting redox homeostasis and STAT3-PI3K axis in psoriasis therapy.

Excessive accumulation of reactive oxygen and nitrogen species (RONS) exacerbates inflammatory respo...

KLRB1 and IL12RB1 are pretherapeutic predictors of time to relapse in patients with psoriasis treated with IL-17 blockade.

BACKGROUND: Relapse of psoriasis after the cessation of treatment remains an unresolved clinical cha...

Artificial intelligence powered mobile health apps for skin cancer detection: current challenges and a systems thinking approach for improved public health outcomes in low- and middle-income countries.

Artificial intelligence (AI) powered mobile health (mHealth) apps are emerging as vital self-triage ...

Deep learning-reconstructed hepatobiliary MRI: Enhancing biliary delineation, lesion margin sharpness, and small lesion detection.

OBJECTIVE: To evaluate the comparative performance of a deep learning-reconstructed T1-weighted volu...

Artificial intelligence for TNM staging in NSCLC: a critical appraisal of segmentation utility in [1⁸F]FDG PET/CT.

PURPOSE: This study aims to investigate whether a diagnostic AI model can effectively support lesion...

Unsupervised SAM-guided mixture-of-multimodal-experts fusion network for medical image diagnosis.

Accurate diagnosis of cancer from medical images relies on both precise lesion localization and comp...