Alle Papers – KI in der Krebserkennung

The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World

Ultrasound Computer-Aided Diagnosis (CAD) Based on the Thyroid Imaging Reporting and Data System (TI-RADS) to Distinguish Benign from Malignant Thyroid Nodules and the Diagnostic Performance of Radiologists with Different Diagnostic Experience

Detection of clustered microcalcifications in small field digital mammography

MCRNet: Multi-level context refinement network for semantic segmentation in breast ultrasound imaging

The influence of mammogram acquisition on the mammographic density and breast cancer association in the mayo mammography health study cohort

Adversarial Deep Structural Networks for Mammographic Mass Segmentation

Reader variability in reporting breast imaging according to BI-RADS® assessment categories (the Florence experience)

Recent Application of Artificial Intelligence in Non-Gynecological Cancer Cytopathology: A Systematic Review

Trial Designs for Personalizing Cancer Care: A Systematic Review and Classification

A computer-aided diagnosis system for malignant melanomas

Skin Cancer Recognition by Using a Neuro-Fuzzy System

Deep Learning for the Detection of Acute Lymphoblastic Leukemia Subtypes on Microscopic Images: A Systematic Literature Review

A survey on histological image analysis-based assessment of three major biological factors influencing radiotherapy: proliferation, hypoxia and vasculature

An unsupervised GVF snake approach for white blood cell segmentation based on nucleus

Entropy-based texture analysis of chromatin structure in advanced prostate cancer

Decoding the molecular subtypes of breast cancer seen on multimodal ultrasound images using an assembled convolutional neural network model: A prospective and multicentre study

Analytical performance of HPV assays on vaginal self-collected vs practitioner-collected cervical samples: the SCoPE study

Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology

Generating Synthetic Data for Medical Imaging

Weakly Supervised Multi-Task Learning for Cell Detection and Segmentation

Influence of gray level and space discretization on brain tumor heterogeneity measures obtained from magnetic resonance images

Hematologist‐Level Classification of Mature B‐Cell Neoplasm Using Deep Learning on Multiparameter Flow Cytometry Data

Remote Diagnosis and Triaging Model for Skin Cancer Using EfficientNet and Extreme Gradient Boosting

Formal methods for prostate cancer Gleason score and treatment prediction using radiomic biomarkers

DTI based Alzheimer’s disease classification with rank modulated fusion of CNNs and random forest