Dermatology

Bifunctional robots inducing targeted protein degradation.

The gaining importance of Targeted Protein Degradation (TPD) and PROTACs (PROteolysis-TArgeting Chim...

Evaluation of Semiautomatic and Deep Learning-Based Fully Automatic Segmentation Methods on [F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization.

The objective is to assess the performance of seven semiautomatic and two fully automatic segmentati...

Artificial intelligence-derived dermatology case reports are indistinguishable from those written by humans: A single-blinded observer study.

Interactive Explainable Deep Learning Model Informs Prostate Cancer Diagnosis at MRI.

Background Clinically significant prostate cancer (PCa) diagnosis at MRI requires accurate and effic...

Current developments and perspectives in psoriasis.

The study of psoriasis has yielded fundamental new insights into immunologic regulation and innovati...

New Generation of 3D Virtual Models with Perfusional Zones: Perioperative Assistance for the Best Pedicle Management during Robotic Partial Nephrectomy.

Selective clamping during robot-assisted partial nephrectomy (RAPN) may reduce ischemia-related func...

DeepNAPSI multi-reader nail psoriasis prediction using deep learning.

Nail psoriasis occurs in about every second psoriasis patient. Both, finger and toe nails can be aff...

Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.

OBJECTIVES: To evaluate image quality, diagnostic acceptability, and lesion conspicuity in abdominal...

Investigation of radiomics and deep convolutional neural networks approaches for glioma grading.

To determine glioma grading by applying radiomic analysis or deep convolutional neural networks (DCN...

Integrating single-cell analysis and machine learning to create glycosylation-based gene signature for prognostic prediction of uveal melanoma.

BACKGROUND: Increasing evidence suggests a correlation between glycosylation and the onset of cancer...

Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method.

The purpose is to evaluate whether deep learning-based denoising (DLD) algorithm provides sufficient...

Thin-slice Two-dimensional T2-weighted Imaging with Deep Learning-based Reconstruction: Improved Lesion Detection in the Brain of Patients with Multiple Sclerosis.

PURPOSE: Brain MRI with high spatial resolution allows for a more detailed delineation of multiple s...

Artificial Intelligence-Based Psoriasis Severity Assessment: Real-world Study and Application.

BACKGROUND: Psoriasis is one of the most frequent inflammatory skin conditions and could be treated ...

Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer.

BACKGROUND: Dose escalation radiotherapy enables increased control of prostate cancer (PCa) but requ...

Differentiating malignant and benign eyelid lesions using deep learning.

Artificial intelligence as a screening tool for eyelid lesions will be helpful for early diagnosis o...

EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation.

Although various methods based on convolutional neural networks have improved the performance of bio...

Hyperspectral imaging-based cutaneous wound classification using neighbourhood extraction 3D convolutional neural network.

OBJECTIVES: Hyperspectral imaging is an emerging imaging modality that beginning to gain attention f...

A novel deep learning model for breast lesion classification using ultrasound Images: A multicenter data evaluation.

PURPOSE: Breast cancer is one of the major reasons of death due to cancer in women. Early diagnosis ...

Robot-assisted sacrohysteropexy vs robot-assisted sacrocolpopexy in women with primary advanced apical prolapse: A retrospective cohort study.

BACKGROUND: This study aimed to evaluate the anatomic and clinical outcomes of robot-assisted sacroh...

A deep-learning algorithm to classify skin lesions from mpox virus infection.

Undetected infection and delayed isolation of infected individuals are key factors driving the monke...

Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) af...