Dermatology

A Multitask Deep Learning Approach for Tumor Segmentation and Morphological Quantification in Acral Melanoma Whole-Slide Images.

This study presents an integrated multitask deep learning framework for the automated analysis of acral melanoma from whole-slide images (WSIs). We constructed a multiscale WSI dataset with pixel-level annotations and developed a pipeline that sequentially performs classification, segmentation, and morphological quantification. An optimized ResNet50 classifier first screens for malignancy. For mal...

Transformer-based super-resolution lung CT images improve visualization of multiple diseases.

OBJECTIVES: To assess the Transformer-based Swin2SR model for super-resolution (SR) enhancement of lung CT images and its clinical potential. METHODS: Chest CT scans from 303 patients at three hospitals were retrospectively included. Standard 512-matrix images were enhanced to 1024- and 2048-matrix versions (SR-1024, SR-2048). Image noise and signal-to-noise ratio (SNR) for lung tissue, muscle, an...

Unraveling the toxicological impact of Bisphenol A exposure on dermatomyositis: An integration of network toxicology and machine learning approaches.

BACKGROUND: Dermatomyositis is a common immune-mediated skin disorder whose pathogenesis has not been fully elucidated. Environmental factors play a k...

Scratcher: An automated machine-vision tool for dissecting the neural basis of itch.

Itch or pruritus invokes a specific reflexive and repetitive directed nocifensive behavioural response, known as scratching. Recent decades have revea...

Domain specific multimodal large language model for automated endoscopy reporting with multicenter prospective validation.

Accurate endoscopy reports are crucial for the diagnosis and management of patients with upper gastrointestinal (UGI) diseases, yet errors and omissio...

Deep learning-based infrared thermography reveals reproducible uniform and individual thermoregulatory responses during running.

Infrared thermography (IRT) has recently gained attention in the field of exercise physiology, due to its ability to monitor thermoregulatory and card...

KM-DBSCAN: an enhanced density and centroid based border detection framework for data reduction towards green AI.

Green AI aims to design and train machine learning models while taking into consideration sustainable resource usage without sacrificing model efficie...

Potential of SERS and proteomics for biomarker detection in cancer cells.

This study investigates the use of quantitative LC-MS/MS-based proteomics and surface-enhanced Raman spectroscopy (SERS) for biomarker detection in cl...

Dental Odontogenic Lesion CBCT and Histopathology Integrated Dataset for Benchmarking Deep Learning Algorithms.

Accurate diagnosis of odontogenic lesions requires pre-operative cone-beam computed tomography (CBCT) and post-operative histopathological confirmatio...

Waveformer: Dual-Branch Adaptive Network with Wavelet-Guided Cross-Context Decoding for Colorectal Polyp Segmentation.

With the advancement of deep learning, polyp segmentation in endoscopic images has achieved remarkable progress. However, clinical polyps often exhibi...

Novel two-stage deep learning framework for automated pressure injury classification.

OBJECTIVE: The study aims to develop an artificial intelligence (AI) framework for automatic pressure injury (PI) staging directly from raw clinical i...

Multimodal CT Perfusion-Based Deep Learning for Predicting Stroke Lesion Outcomes in Complete and No Recanalization Scenarios.

BACKGROUND AND PURPOSE: Predicting the final location and volume of lesions in acute ischemic stroke is crucial for clinical management. While CTP is ...

GIS-based neural network framework for zoonotic cutaneous leishmaniasis risk mapping in Western Iran.

This study presents a Geospatial Artificial Intelligence (GeoAI) framework for high-resolution Zoonotic Cutaneous Leishmaniasis (ZCL) risk mapping, co...

Distinctive DNA sequence features define epigenetic longevity of inflammatory memory.

Tissues harbor memories of inflammation, which heighten sensitivity to diverse future assaults. Whether and how these adaptations are sustained throug...

Quality, Empathy, and Readability of AI Chatbot Responses to the Survivorship Needs of Adolescents and Young Adults With Melanoma: Evaluation Study.

BACKGROUND: Melanoma, a highly aggressive form of skin cancer, is the second most common type of cancer for adolescent and young adult (AYA, ages 15-3...

Reducing breath-hold time in liver MRI: Clinical performance of deep learning-accelerated post-contrast T1 VIBE sequences.

BACKGROUND: Post-contrast liver MRI often requires long breath-holds, risking motion artifacts that can reduce diagnostic quality. We assessed whether...

Bone Metastasis Detection at CT with Deep Learning Models Trained Using Multicenter, Multimodal Reference Standards: Development and Evaluation.

Purpose To develop and validate deep learning models for detecting bone metastases on abdominal and thoracic CT scans, considering lesion visibility, ...

Prospective Evidence on Artificial Intelligence-Assisted Melanoma Diagnostics: A Systematic Review and Meta-Analysis.

IMPORTANCE: Dermoscopy is a standard of care for melanoma diagnostics, and artificial intelligence (AI) systems are increasingly investigated as decis...

Framing bias in a large language model: Prompt framing influences ChatGPT's accuracy in melanoma classification. A diagnostic accuracy study.

Ti3C2/CuCoSe2 p-n Heterojunction: Preparation and Mechanism for Machine Learning-enhanced Electrochemical Sensing of Rutin.

Rutin is widely employed as a therapeutic agent, but excessive intake may induce adverse reactions such as gastric discomfort, headache and dermatitis...