Dermatology

Artificial intelligence for automatic detection of basal cell carcinoma from frozen tissue tangential biopsies.

Evaluation of basal cell carcinoma (BCC) involves tangential biopsies of a suspicious lesion that is...

Using artificial intelligence-based technologies to support the diagnosis and early detection of melanoma in primary care.

Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial.

BACKGROUND: Use of artificial intelligence (AI), or machine learning, to assess dermoscopic images o...

Performance evaluation of ML models for preoperative prediction of HER2-low BC based on CE-CBBCT radiomic features: A prospective study.

To explore the value of machine learning (ML) models based on contrast-enhanced cone-beam breast com...

[Artificial intelligence research advances in discrimination and diagnosis of pulmonary ground-glass nodules].

Lung cancer, which accounts for about 18% of all cancer-related deaths worldwide, has a dismal 5-yea...

[Exploration of prognostic models for chronic rhinosinusitis with nasal polyps based on machine learning].

To analysis the molecular characteristics of chronic rhinosinusitis with nasal polyps (CRSwNP), to ...

Artificial dermatitis versus artificial intelligence: Detecting etiology with Google Lens.

Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism.

This manuscript presents a comprehensive investigation into the role of lactate metabolism-related g...

A novel deep learning framework for accurate melanoma diagnosis integrating imaging and genomic data for improved patient outcomes.

BACKGROUND: Melanoma is one of the most malignant forms of skin cancer, with a high mortality rate i...

Current State of Dermatology Mobile Applications With Artificial Intelligence Features.

IMPORTANCE: With advancements in mobile technology and artificial intelligence (AI) methods, there h...

Comprehensive single-cell RNA-seq analysis using deep interpretable generative modeling guided by biological hierarchy knowledge.

Recent advances in microfluidics and sequencing technologies allow researchers to explore cellular h...

From machine learning to clinical practice: phenotypic clusters of anti-MDA5 antibody-positive dermatomyositis.

Ethical considerations for artificial intelligence in dermatology: a scoping review.

The field of dermatology is experiencing the rapid deployment of artificial intelligence (AI), from ...

Comprehensive analysis of clinical images contributions for melanoma classification using convolutional neural networks.

BACKGROUND: Timely diagnosis plays a critical role in determining melanoma prognosis, prompting the ...

Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI.

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with system...

Hybrid cosmetic dermatology: AI generated horizon.

[Applications of Artificial Intelligence in Pancreatic Cystic Lesion Imaging].

As the detection rate of pancreatic cystic lesions(PCL)increases,artificial intelligence(AI)has made...

Image-based remote evaluation of PASI scores with psoriasis by the YOLO-v4 algorithm.

As a chronic relapsing disease, psoriasis is characterized by widespread skin lesions. The Psoriasis...

Facial adult female acne in China: An analysis based on artificial intelligence over one million.

BACKGROUND: To further clarify the acne profile of Chinese adult women, we included 1,156,703 adult ...

D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.

As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal g...

[Screening for Characteristic Genes of Different Traditional Chinese Medicine Syndromes of Psoriasis Vulgaris: A Study Based on Bioinformatics and Machine Learning].

OBJECTIVE: To screen for the key characteristic genes of the psoriasis vulgaris (PV) patients with d...