AIMC Topic: Humans

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Leveraging machine learning techniques for image classification and revealing social media insights into human engagement with urban wild spaces.

Scientific reports
In recent years, machine learning models have exhibited excellent performance and far-reaching impact across domains such as fraud detection in finance, recommendation systems in e-commerce, medical imaging in healthcare, agricultural forecasting, so...

Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations.

Scientific reports
Super-resolution imaging has emerged as a rapidly advancing field in diagnostic ultrasound. Ultrasound Localization Microscopy (ULM) achieves sub-wavelength precision in microvasculature imaging by tracking gas microbubbles (MBs) flowing through bloo...

AI based natural inhibitor targeting RPS20 for colorectal cancer treatment using integrated computational approaches.

Scientific reports
The increasing global incidence of cancer emphasizes the vital role of machine learning algorithms and artificial intelligence (AI) in identifying novel anticancer targets and developing new drugs. Computational approaches can significantly quicken r...

Autoimmune gastritis detection from preprocessed endoscopy images using deep transfer learning and moth flame optimization.

Scientific reports
Gastric Tract Disease (GTD) constitutes a medical emergency, emphasizing the critical importance of early diagnosis and intervention to lessen its severity. Clinical practices often utilize endoscopy-supported examinations for GTD screening. The imag...

Mapping the colon through the colonoscope's coordinates - The Copenhagen Colonoscopy Coordinate Database.

Scientific data
Colonoscopy is the leading endoscopic technique when it comes to implementing artificial intelligence-based tools to optimize the procedure. However, no database consisting of the colonoscope's coordinates exists, allowing for a mapping with timestam...

PediMS: A Pediatric Multiple Sclerosis Lesion Segmentation Dataset.

Scientific data
Multiple Sclerosis (MS) is a chronic autoimmune disease that primarily affects the central nervous system and is predominantly diagnosed in adults, making pediatric cases rare and underrepresented in medical research. This paper introduces the first ...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

Nature communications
While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence ...

PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.

BMJ open
INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety or obsessive-compulsive disorders. Nonetheless, a substantial proportion of patients do not experien...

Theory-based chatbot for promoting colorectal cancer screening in a community setting in Hong Kong: study protocol of a randomised controlled trial.

BMJ open
BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer mortality worldwide. Despite the organised CRC screening programme, the uptake rate of the population-based CRC screening was still low. Thus, ...

Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol.

BMJ health & care informatics
INTRODUCTION: Multimorbidity (MM), defined as two or more chronic diseases in an individual, is linked to adverse outcomes. MM is increasing in sub-Saharan Africa due to rapidly advancing epidemiological and social transitions. The Research Hub (MAD...