Dermatology

Prediction of Epidermal Growth Factor Receptor Mutation Subtypes in Non-Small Cell Lung Cancer From Hematoxylin and Eosin-Stained Slides Using Deep Learning.

Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype is critical for the treatment of non-small cell lung cancer patients. Conventional molecular testing methods for detecting EGFR mutations have limitations. In this study, an artificial intelligence-powered deep learning framework was developed for the weakly supervised prediction of EGFR mutations in non-sma...

Utilization of machine learning for dengue case screening.

Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To address this, artificial intelligence tools like machine learning can play a crucial role in developing more effective strategies for control, diagnosis, and treatment. This study identifies relevant variables for the screening of dengue cases throu...

Contrastive Learning vs. Self-Learning vs. Deformable Data Augmentation in Semantic Segmentation of Medical Images.

To develop a robust segmentation model, encoding the underlying features/structures of the input data is essential to discriminate the target structur...

HTC-retina: A hybrid retinal diseases classification model using transformer-Convolutional Neural Network from optical coherence tomography images.

Retinal diseases are among nowadays major public health issues, deservedly needing advanced computer-aided diagnosis. We propose a hybrid model for mu...

Preservative contact allergy in occupational dermatitis: a machine learning analysis.

Occupational dermatoses impose a significant socioeconomic burden. Allergic contact dermatitis related to occupation is prevalent among healthcare wor...

Automatic evaluation of Nail Psoriasis Severity Index using deep learning algorithm.

Nail psoriasis is a chronic condition characterized by nail dystrophy affecting the nail matrix and bed. The severity of nail psoriasis is commonly as...

Development of a machine learning-based model for predicting positive margins in high-grade squamous intraepithelial lesion (HSIL) treatment by Cold Knife Conization(CKC): a single-center retrospective study.

OBJECTIVES: This study aims to analyze factors associated with positive surgical margins following cold knife conization (CKC) in patients with cervic...

Deep learning-based prediction of compressive strength of eco-friendly geopolymer concrete.

The greenhouse gases cause global warming on Earth. The cement production industry is one of the largest sectors producing greenhouse gases. The geopo...

Deep Learning Models of Multi-Scale Lesion Perception Attention Networks for Diagnosis and Staging of Pneumoconiosis: A Comparative Study with Radiologists.

Accurate prediction of pneumoconiosis is essential for individualized early prevention and treatment. However, the different manifestations and high h...

Enhancing Skin Cancer Diagnosis Using Swin Transformer with Hybrid Shifted Window-Based Multi-head Self-attention and SwiGLU-Based MLP.

Skin cancer is one of the most frequently occurring cancers worldwide, and early detection is crucial for effective treatment. Dermatologists often fa...

Optimized attention-induced multihead convolutional neural network with efficientnetv2-fostered melanoma classification using dermoscopic images.

Melanoma is an uncommon and dangerous type of skin cancer. Dermoscopic imaging aids skilled dermatologists in detection, yet the nuances between melan...

TumFlow: An AI Model for Predicting New Anticancer Molecules.

Melanoma is the fifth most common cancer in the United States. Conventional drug discovery methods are inherently time-consuming and costly, which imp...

Diagnosing contact dermatitis using machine learning: A review.

BACKGROUND: Machine learning (ML) offers an opportunity in contact dermatitis (CD) research, where with full clinical picture, may support diagnosis a...

Automatized self-supervised learning for skin lesion screening.

Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists...

GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status.

Noninvasively and accurately predicting the epidermal growth factor receptor (EGFR) mutation status is a clinically vital problem. Moreover, further i...

MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3-D CT Lesions.

With the renaissance of deep learning, automatic diagnostic algorithms for computed tomography (CT) have achieved many successful applications. Howeve...

Hybrid CNN-Transformer Network With Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-Contrast CT Scans.

Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS). Non-contrast CT (NCCT) is still a mainstream imaging modal...

Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma.

The functions of immunosenescence are closely related to skin cutaneous melanoma (SKCM). The aim of this study is to uncover the characteristics of im...

Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma.

BACKGROUND: Psoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicat...

Automated Prediction of Malignant Melanoma using Two-Stage Convolutional Neural Network.

PURPOSE: A skin lesion refers to an area of the skin that exhibits anomalous growth or distinctive visual characteristics compared to the surrounding ...