Dermatology

BiCervi: Pap smear microscopy image dataset for cervical cancer detection and classification.

Cervical cancer is still a major public-health challenge, especially in low and middle-income countries where there are limited numbers of specialists to review Pap smears. While Pap smear screening is widely used, manual reading is slow and can vary from one expert to another, which makes data-driven decision support increasingly important. However, Pap smear imagery datasets from African screeni...

Smartphone Applications in Dermatology With Special Focus on AI: A European-Continent-Based Review.

Smartphone applications for dermatology are widely available across Europe, yet evidence on their characteristics, validation, and regulatory compliance remains limited. This review, conducted by the European Academy of Dermatology and Venereology (EADV) Artificial Intelligence (AI) Task Force, systematically searched app stores in 44 European countries, identifying 1746 apps in 2024, of which 420...

Development of a predictive marker panel for the individualised bDMARD therapy of psoriatic arthritis: protocol for a prospective observational study (Integrate-PsA).

INTRODUCTION: Psoriatic arthritis is a chronic inflammatory disease that can affect the axial skeleton as well as the joints and enthesis. Following t...

Image optimization for low-dose 18F-FDG breast PET/MRI using deep learning: a pilot study.

BACKGROUND: Positron emission tomography with magnetic resonance imaging (PET/MRI) provides noninvasive molecular characterization of breast cancer an...

Dual AI models for gamma knife radiosurgery in craniopharyngioma: prescription dose modeling and outcome risk prediction.

BACKGROUND: Gamma Knife radiosurgery (GKRS) is an established adjunct for residual or recurrent craniopharyngioma, yet prescription dose selection rem...

A modern review of uveal melanoma: molecular insights, clinical management, and emerging therapies.

Uveal melanoma is the most frequent primary intraocular malignancy in adults and is characterized by an aggressive clinical course, high propensity fo...

Deep progressive learning reconstruction for fast and low-dose whole-body PET scans in an integrated PET/MR system.

BACKGROUND: PET/MR combines molecular and functional imaging but faces challenges such as prolonged scans, noise from reduced tracer activity, and sub...

Deep learning reconstruction-applied PROPELLER diffusion-weighted imaging in uterine malignancies: a comparison study with MUSE.

PURPOSE: To compare the image quality of diffusion-weighted imaging (DWI) between deep learning reconstruction (DLR)-applied Periodically Rotated Over...

Maintaining SUV accuracy in low-count PET with PETfectior: a deep learning denoising solution.

The diagnostic image quality of positron emission tomography (PET) acquisitions strongly depends on the administered radiotracer activity and acquisit...

Automated model-based lesion tracking in CT: colorectal liver metastases as a use case for development and performance analysis.

OBJECTIVE: To develop and evaluate an automated CT liver lesion-tracking algorithm that matches lesions over time, detects new metastases, and reports...

Frontline Health Workers' Perspectives of the World Health Organization Skin Neglected Tropical Diseases App in Kenya: Qualitative Study on AI-Embedded mHealth Implementation.

BACKGROUND: Skin neglected tropical diseases (NTDs) pose significant diagnostic and management challenges in resource-limited settings due to constrai...

Paintable on-skin dry electrodes with robust skin and device connection for wireless sensing and human-machine interfaces.

Reliable and continuous electrophysiological recording is important for health monitoring and human-machine interactions. However, most existing epide...

Label-Free Prediction of EGFR Mutation Status Using Fluorescence Lifetime Imaging and Deep Learning in Lung Adenocarcinoma.

UNLABELLED: Accurate prediction of epidermal growth factor receptor (EGFR) mutations is essential for guiding targeted therapy in non-small cell lung ...

Machine learning modeling to predict HCC locations in cirrhotic patients undergoing MRI - a proof-of-concept study.

PURPOSE: Current hepatocellular carcinoma (HCC) surveillance guidelines rely on manually defined LI-RADS (Liver Imaging Reporting and Data System) fea...

AI-Based Diagnostic Platform Capabilities With Lyme Disease as a Use Case: Integrative Exploration.

BACKGROUND: Lyme disease (LD) is the most common vector-borne disease in the United States. It is difficult to diagnose because it can mimic numerous ...

Tri-Net: unified deep learning for skin lesion and symptom-based monkeypox detection.

The recent re-emergence of Monkeypox emphasizes the critical importance of ensuring precise and prompt diagnostic capabilities. Traditional diagnosis ...

Transcriptomic characterization of key psoriasis-associated genes based on single-cell RNA-seq and machine learning.

BACKGROUND: Psoriasis is a multifaceted skin and systemic disorder driven by a complex interplay of genetic, immunological, and environmental factors....

Intratumoral distribution of anisokaryosis in canine cutaneous mast cell tumors.

Automated measurements of anisokaryosis in canine cutaneous mast cell tumors (ccMCTs) have been shown to be predictive of survival, but questions rema...

Evaluation of deep learning-based reconstruction models on non-TOF BGO PET/CT: impact of acquisition times and BSREM penalization factors on lesion detectability and SNR.

BACKGROUND: New long field-of-view (FOV) PET scanners using bismuth germanate (BGO) detectors without time-of-flight (TOF) capability are now availabl...

MoMBS: Mixed-order sampling improves training on heterogeneous-quality data for universal lesion detection.

Universal lesion detection (ULD) in computed tomography plays an essential role in computer-aided diagnosis. However, images in ULD tasks often exhibi...