Dermatology

Artificial Intelligence-Driven Segmentation of Three Oral Diseases: Enabling Precision Diagnosis and Decision Support.

INTRODUCTION: The advancement of AI-assisted oral disease diagnosis critically relies on the availability of annotated, high-quality datasets and resilient deep learning architectures. Nevertheless, progress in this domain has been impeded by the scarcity of publicly accessible data and inadequate benchmarking of existing models. To address these limitations, we introduced a meticulously curated d...

Boosting foundation models for rare eye disease diagnosis via a multimodal text-to-image generative framework.

The rising prevalence of vision-threatening retinal diseases poses a significant burden on the global healthcare systems. Though deep learning (DL) techniques offer promising avenues for improving diagnostic efficiency, data scarcity and imbalance issues persist in training robust diagnostic models, particularly for rare eye diseases. Here, we introduce EyeDiff, a generative foundation model capab...

Clinical priors-inspired privileged knowledge distillation for reliable pancreatic lesion classification.

Accurate classification of pancreatic lesions is critical for guiding treatment decisions, with computed tomography (CT) being the primary modality ow...

Microneedle-based theranostics for melanoma: Advances and outlook.

Melanoma represents a highly aggressive malignancy that poses persistent challenges for clinical diagnosis and treatment. Although surgical interventi...

The evolution of T1-weighted lesion inpainting tools in patients with brain injury: A scoping review.

Focal brain lesions from Acquired Brain Injuries (ABIs) present as regions of abnormal signal intensity on T1-weighted Magnetic Resonance Imaging (MRI...

Multidimensional data analysis and classification using SMIAL.

Label-free imaging enables multidimensional data acquisition across spectral and temporal domains and is increasingly used in life sciences. However, ...

An interpretable machine learning model for early risk stratification of medium-to-giant coronary artery aneurysm in Kawasaki disease: development and external validation.

BACKGROUND: Medium-to-giant coronary artery aneurysm (MGCAA) represents the most severe complication of Kawasaki disease (KD) and remains difficult to...

Artificial intelligence in atopic dermatitis: Current applications and future perspectives.

Atopic dermatitis (AD) is a prevalent and burdensome chronic skin disease, with profound effects on patient quality of life. Advancing its diagnosis a...

Deep learning-based segmentation of aneurysmal subarachnoid hemorrhage: toward accurate and scalable prognostic imaging.

BACKGROUND: Accurate segmentation of aneurysmal cerebral hemorrhages, including subarachnoid hemorrhage (SAH), intraparenchymal hemorrhage (IPH), and ...

Enhancing pulmonary embolism diagnosis: a squeeze-and-attention U-Net for precise detection and segmentation in CT angiography.

OBJECTIVE: Pulmonary embolism (PE) is a life-threatening condition requiring rapid and accurate diagnosis. This study proposes a deep learning-based a...

Q-CaDD: accelerating in silico methodologies with quantum computation and machine learning for Epidermal growth factor receptor.

MRI-based AI framework for predicting lymph node metastasis and prognosis in rectal cancer after neoadjuvant chemoradiotherapy: a multicenter study.

BACKGROUND: Early prediction of lymph node metastasis (LNM) after neoadjuvant chemoradiotherapy (nCRT) is crucial for improving treatment planning and...

Integrating bioinformatics, machine learning and molecular biology to elucidate the anti-allergic mechanisms of ginkgo biloba leaves.

Allergic diseases, encompassing allergic asthma, atopic dermatitis, food allergies, have emerged as substantial global public health challenges, with ...

Machine Learning Predicts Adequacy of Rapid On-site Evaluation in Fine Needle Aspirations in Lung Cancer Cytology.

Lung cancer is projected to become the leading cause of cancer-related mortality in both smoking and nonsmoking populations. Rapid on-site evaluation ...

Biophysical properties and phenotypes of cell clusters detached from Staphylococcus epidermidis biofilms after matrix-targeted disruption.

Bacterial cells detached from Staphylococcus epidermidis biofilms are found to release predominantly as small oblate clusters (∼1.9 µm) in both untrea...

Bulliform cells: anatomical, physiological, genetic, and computational perspectives on plants' drought adaptation.

This work highlights pollen thermotolerance as vital for reproductive success under heat stress, integrating molecular regulation, gene mapping, and b...

Multimodal models for skin cancer classification using clinical freetext and dermatoscopic images.

BACKGROUND: Skin cancer is one of the most prevalent cancers globally, with early detection critical to ensure reduced mortality risk. To aid early de...

Automated classification of site-specific cutaneous photodamage using a convolutional neural network and three-dimensional total body photography.

BACKGROUND: Early detection of melanoma presents a major public health challenge. Growing evidence supports targeted surveillance of individuals at hi...

Inflammatory protein profiling in immune cells identifies molecular signatures for enhanced diagnostic precision in psoriatic arthritis.

Psoriatic arthritis (PsA) lacks reliable biomarkers to support early diagnosis and disease stratification. This study aimed to identify protein signat...

Operationalising One Health for epidermal parasitic skin diseases: threshold-triggered mass drug administration and a minimal indicator set.

Epidermal parasitic skin diseases (EPSDs)-including scabies, pediculosis, cutaneous leishmaniasis, tungiasis and cutaneous larva migrans-affect millio...