Dermatology

Exploring indigenous South African plants as alternative treatments for dermatophytosis: Focusing on the antifungal properties and mechanism of action of Searsia lancea.

Numerous medicinal plants are reported to have activity against dermatophytes, however, there are limited studies providing insights into their mechanism of action, which may be hindering their clinical use. This study aimed to investigate the antifungal activity and toxicity of three South African plants traditionally used to treat skin infections caused by dermatophytes and to investigate the me...

Non-proliferative diabetic retinopathy detection using Rosmarus Quagga optimized explainable generative meta learning based deep convolutional neural network model.

PURPOSE: Non-Proliferative Diabetic Retinopathy (NPDR) is a complication of diabetes disease where there is damage of the blood vessels in retina but with no signs of formation of new vessels. It is present in the earlier stages and therefore the control of diabetes combined with constant check-up can address the challenge. Existing models face several challenges such as heterogeneity of the lesio...

Isolation and characterization of a bioactive compound from Sphingomonas sanguinis DM with cytotoxic and molecular docking analysis.

Datura metel, a common plant in the Solanaceae family, is known for its valuable medicinal properties. The metabolites created by its rhizosphere bact...

Evaluating the Diagnostic and Treatment Capabilities of GPT-4 Vision in Dermatology: A Pilot Study.

BACKGROUND: The integration of generative artificial intelligence within dermatology presents a new frontier for enhancing diagnostic accuracy and tre...

Artificial Intelligence Performs Well for Patient-Level Education of Benign Anorectal Conditions.

BackgroundChatGPT, the most widely recognized AI chatbot, has been increasingly utilized by patients for health care education, but its performance an...

A Lesion-Fusion Neural Network for Multi-View Diabetic Retinopathy Grading.

As the most common complication of diabetes, diabetic retinopathy (DR) is one of the main causes of irreversible blindness. Automatic DR grading plays...

Machine learning-based text mining for cutaneous myiasis and potential value of an accidental maggot therapy for complicated skin and soft tissue infection with sepsis.

BACKGROUND: Cutaneous myiasis, one of the most frequently diagnosed myiasis types, is defined as skin or soft tissue on a living host infested by dipt...

An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification.

Skin lesions remain a significant global health issue, with their incidence rising steadily over the past few years. Early and accurate detection is c...

Synthetic medical education in dermatology leveraging generative artificial intelligence.

The advent of large language models (LLMs) represents an enormous opportunity to revolutionize medical education. Via "synthetic education," LLMs can ...

Optimizing stroke lesion segmentation: A dual-approach using Gaussian mixture models and nnU-Net.

Machine learning-based stroke lesion segmentation models are widely used in biomedical imaging, but their ability to detect treatment effects remains ...

Video-Based Multiphysiological Disentanglement and Remote Robust Estimation for Respiration.

Remote noncontact respiratory rate estimation by facial visual information has great research significance, providing valuable priors for health monit...

Predicting Gene Comutation of EGFR and TP53 by Radiomics and Deep Learning in Patients With Lung Adenocarcinomas.

PURPOSE: This study was designed to construct progressive binary classification models based on radiomics and deep learning to predict the presence of...

The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.

This study investigated the added value of using maximum-intensity projection (MIP) images for fully automatic segmentation of lesions using deep lear...

Machine learning in prediction of epidermal growth factor receptor status in non-small cell lung cancer brain metastases: a systematic review and meta-analysis.

BACKGROUND: Epidermal growth factor receptor (EGFR) mutations are present in 10-60% of all non-small cell lung cancer (NSCLC) patients and are associa...

Global burden of non-melanoma skin cancers among older adults: a comprehensive analysis using machine learning approaches.

Non-melanoma skin cancers (NMSCs), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), have shown significant global increases in ...

Integrating Artificial Intelligence in Dermatological Cancer Screening and Diagnosis: Efficacy, Challenges, and Future Directions.

Skin cancer is the most common cancer in the United States, with incidence rates continuing to rise both nationally and globally, posing significant h...

Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis.

BACKGROUND: The "gut-skin axis" has been proposed to play an important role in the development and symptoms of atopic dermatitis. Therefore, we have c...

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-m...

Challenges, optimization strategies, and future horizons of advanced deep learning approaches for brain lesion segmentation.

Brain lesion segmentation is challenging in medical image analysis, aiming to delineate lesion regions precisely. Deep learning (DL) techniques have r...

SkinEHDLF a hybrid deep learning approach for accurate skin cancer classification in complex systems.

Skin cancer represents a significant global public health issue, and prompt and precise detection is essential for effective treatment. This study int...