AIMC Topic: Artificial Intelligence

Clear Filters Showing 11221 to 11230 of 26332 articles

Relationship between a deep learning model and liquid-based cytological processing techniques.

Cytopathology : official journal of the British Society for Clinical Cytology
OBJECTIVE: Artificial intelligence (AI)-based cytopathology studies conducted using deep learning have enabled cell detection and classification. Liquid-based cytology (LBC) has facilitated the standardisation of specimen preparation; however, cytomo...

Benchmarking explanation methods for mental state decoding with deep learning models.

NeuroImage
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., experiencing anger or joy) and brain activity by identifying those spatial and temporal feat...

Artificial intelligence and real-world data for drug and food safety - A regulatory science perspective.

Regulatory toxicology and pharmacology : RTP
In 2013, the Global Coalition for Regulatory Science Research (GCRSR) was established with members from over ten countries (www.gcrsr.net). One of the main objectives of GCRSR is to facilitate communication among global regulators on the rise of new ...

Do Anthropomorphic Chatbots Increase Counseling Satisfaction and Reuse Intention? The Moderated Mediation of Social Rapport and Social Anxiety.

Cyberpsychology, behavior and social networking
The growing demand for mental health services and artificial intelligence chatbots to replace human agents have led to increased attention to chatbot anthropomorphizing. This study explored the effect of anthropomorphism on counseling satisfaction an...

An Opinion on ChatGPT in Health Care-Written by Humans Only.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine

Tea leaf disease detection and identification based on YOLOv7 (YOLO-T).

Scientific reports
A reliable and accurate diagnosis and identification system is required to prevent and manage tea leaf diseases. Tea leaf diseases are detected manually, increasing time and affecting yield quality and productivity. This study aims to present an arti...

Collaborative training of medical artificial intelligence models with non-uniform labels.

Scientific reports
Due to the rapid advancements in recent years, medical image analysis is largely dominated by deep learning (DL). However, building powerful and robust DL models requires training with large multi-party datasets. While multiple stakeholders have prov...

Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry.

Scientific reports
Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of the most challenging perspectives in the Liquid Biopsy scenario. Here we show a machine learning-powered tomographic phase imaging flow cytometry syst...

[Eight misconceptions about AI in healthcare].

Nederlands tijdschrift voor geneeskunde
It is of paramount importance that healthcare professionals can participate in the academic and societal debate surrounding medical AI. To realise this critical-constructive guidance of AI, it is necessary to be able to distinguish between different ...