Dermatology

Machine Learning Models of Early Longitudinal Toxicity Trajectories Predict Cetuximab Concentration and Metastatic Colorectal Cancer Survival in the Canadian Cancer Trials Group/AGITG CO.17/20 Trials.

PURPOSE: Cetuximab (CET), targeting the epidermal growth factor receptor, is a systemic treatment op...

Pre-trained molecular representations enable antimicrobial discovery.

The rise in antimicrobial resistance poses a worldwide threat, reducing the efficacy of common antib...

Evaluating medical AI systems in dermatology under uncertain ground truth.

For safety, medical AI systems undergo thorough evaluations before deployment, validating their pred...

Exploring 4 generation EGFR inhibitors: A review of clinical outcomes and structural binding insights.

Epidermal growth factor receptor (EGFR) is a potential target for anticancer therapies and plays a c...

Integration of graph neural networks and transcriptomics analysis identify key pathways and gene signature for immunotherapy response and prognosis of skin melanoma.

OBJECTIVE: The assessment of immunotherapy plays a pivotal role in the clinical management of skin m...

Application and research progress of artificial intelligence in allergic diseases.

Artificial intelligence (AI), as a new technology that can assist or even replace some human functio...

Advancements in artificial intelligence for atopic dermatitis: diagnosis, treatment, and patient management.

Atopic dermatitis (AD) is a common and complex skin disease that significantly affects the quality o...

Sub-diffuse Reflectance Spectroscopy Combined With Machine Learning Method for Oral Mucosal Disease Identification.

OBJECTIVES: Oral squamous cell carcinoma (OSCC) is the sixth-highest incidence of malignant tumors w...

Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma.

BACKGROUND: Melanoma (SKCM) is an extremely aggressive form of cancer, characterized by high mortali...

Evaluating the performance of ChatGPT on dermatology board-style exams: A meta-analysis of text-based and image-based question accuracy.

A Systemic Review of Large Language Models and Their Implications in Dermatology.

In computational linguistics, large language models have reached a significant turning point. They h...

MedScale-Former: Self-guided multiscale transformer for medical image segmentation.

Accurate medical image segmentation is crucial for enabling automated clinical decision procedures. ...

Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: Experimental Web-Based Study Among Dermatologists.

BACKGROUND: Artificial intelligence (AI)-enabled decision support systems are critical tools in medi...

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care.

PURPOSE: The use of real-world data (RWD) in oncology is becoming increasingly important for clinica...

Adaptive Dual-Axis Style-Based Recalibration Network With Class-Wise Statistics Loss for Imbalanced Medical Image Classification.

Salient and small lesions (e.g., microaneurysms on fundus) both play significant roles in real-world...

Identification of novel IL17-related genes as prognostic and therapeutic biomarkers of psoriasis using comprehensive bioinformatics analysis and machine learning.

Psoriasis is a common chronic skin disorder with a polygenic background. It is widely acknowledged t...

Improved unsupervised 3D lung lesion detection and localization by fusing global and local features: Validation in 3D low-dose computed tomography.

Unsupervised anomaly detection (UAD) is crucial in low-dose computed tomography (LDCT). Recent AI te...

Predictive models of epidermal growth factor receptor mutation in lung adenocarcinoma using PET/CT-based radiomics features.

BACKGROUND: Lung adenocarcinoma (LAC) comprises a substantial subset of non-small cell lung cancer (...

A novel hybrid feature fusion approach using handcrafted features with transfer learning model for enhanced skin cancer classification.

Skin cancer is a deadly disease and has the highest rising rates globally. It arises from aberrant s...

Prognostic assessment of osteolytic lesions and mechanical properties of bones bearing breast cancer using neural network and finite element analysis.

The management of skeletal-related events (SREs), particularly the prevention of pathological fractu...

Unveiling the power of Treg.Sig: a novel machine-learning derived signature for predicting ICI response in melanoma.

BACKGROUND: Although immune checkpoint inhibitor (ICI) represents a significant breakthrough in canc...