Latest AI and machine learning research in preventive care for healthcare professionals.
According to forecasts, 27 % of the German population will be aged 65 or over by 2050. Age-associated multimorbidity, functional impairment and need for care have a considerable impact on the healthcare system. A comprehensive geriatric assessment (CGA) is therefore essential to identify health risks at an early stage and make targeted treatment decisions. Numerous studies prove effectiveness of C...
This paper introduces an innovative approach for automated polyp segmentation in colonoscopy images, deploying an enhanced Pix2Pix Generative Adversarial Network (GAN) equipped with an integrated attention mechanism in the discriminator. Addressing prevalent challenges in conventional segmentation methods, such as variable polyp appearances, inconsistent image quality, and limited training data, o...
A major challenge in applying deep learning to medical imaging is the paucity of annotated data. This study explores the use of synthetic images for d...
This statement conveys the European Society of Gastrointestinal Endoscopy (ESGE) position on the use of computer-aided detection (CADe) with artificia...
UNLABELLED: The Radiology team from a large Breast Screening Unit in the UK with a screening population of over 135,000 took part in a service evaluat...
BACKGROUND AND OBJECTIVES: Critically ill patients require individualized nutrition support, with assessment tools like Nutrition Risk Screening 2002 ...
The design-make-test cycle for drug discovery is highly dependent on the purification of synthesized compounds. Prior to evaluation of suitability, ul...
Background MRI protocols typically involve many imaging sequences and often require too much time. Purpose To simulate artificial intelligence (AI)-di...
BACKGROUND AND AIMS: Insufficient bowel preparation accounts for up to 42% of missed adenomas in colonoscopy. However, major analysis programs found n...
Lung cancer is one of the leading causes of cancer-related mortality worldwide, with most cases diagnosed at advanced stages where curative treatment ...
Lung cancer is the leading cause of cancer-related mortality worldwide. Early lung cancer detection improves lung cancer-related mortality and surviva...
Distributed and federated learning are important tools for high-dimensional classification of large datasets. To reduce computational costs and over...
Colorectal cancer often arises from precancerous polyps, where accurate size assessment is vital for clinical decisions but challenged by subjective m...
Cancer screening, leading to early detection, saves lives. Unfortunately, existing screening techniques require expensive and intrusive medical proc...
Traditional diagnostic methods like colonoscopy are invasive yet critical tools necessary for accurately diagnosing colorectal cancer (CRC). Detecti...
Breast cancer is a serious public health problem and is one of the leading causes of cancer-related deaths in women worldwide. Early detection of the ...
This study presents a deep learning system for breast cancer detection in mammography, developed using a modified EfficientNetV2 architecture with e...
Multimodal Large Language Models (MLLMs) are of great application across many domains, such as multimodal understanding and generation. With the dev...
Reconstruction kernels in computed tomography (CT) affect spatial resolution and noise characteristics, introducing systematic variability in quanti...
BACKGROUND: Cervical cancer remains a significant global health issue, with accurate differentiation between low-grade (LSIL) and high-grade squamous ...