AIMC Topic: Artificial Intelligence

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A disector-based framework for the automatic optical fractionator.

Journal of chemical neuroanatomy
Stereology-based methods provide the current state-of-the-art approaches for accurate quantification of numbers and other morphometric parameters of biological objects in stained tissue sections. The advent of artificial intelligence (AI)-based deep ...

Advances in Organ-on-a-Chip Materials and Devices.

ACS applied bio materials
The organ-on-a-chip (OoC) paves a way for biomedical applications ranging from preclinical to clinical translational precision. The current trends in the in vitro modeling is to reduce the complexity of human organ anatomy to the fundamental cellular...

Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review.

Systematic reviews
BACKGROUND: In recent years, innovations in artificial intelligence (AI) have led to the development of new healthcare AI (HCAI) technologies. Whilst some of these technologies show promise for improving the patient experience, ethicists have warned ...

Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM).

BMC medical informatics and decision making
BACKGROUND: Evaluating patients' experiences is essential when incorporating the patients' perspective in improving healthcare. Experiences are mainly collected using closed-ended questions, although the value of open-ended questions is widely recogn...

[The effects of the deployment of artificial intelligence on the healthcare professions].

Soins; la revue de reference infirmiere
Understanding the effects of the spread of artificial intelligence and robotization on the healthcare professions must be free of prejudice. In this way, it will be possible to promote a real methodology for evaluating and supporting these transforma...

Explainable Artificial Intelligence-Based IoT Device Malware Detection Mechanism Using Image Visualization and Fine-Tuned CNN-Based Transfer Learning Model.

Computational intelligence and neuroscience
Automated malware detection is a prominent issue in the world of network security because of the rising number and complexity of malware threats. It is time-consuming and resource intensive to manually analyze all malware files in an application usin...

Human-machine collaboration using artificial intelligence to enhance the safety of donning and doffing personal protective equipment (PPE).

Infection control and hospital epidemiology
OBJECTIVES: To compare the accuracy of monitoring personal protective equipment (PPE) donning and doffing process between an artificial intelligent (AI) machine collaborated with remote human buddy support system and an onsite buddy, and to determine...

Digital skills of therapeutic radiographers/radiation therapists - Document analysis for a European educational curriculum.

Radiography (London, England : 1995)
INTRODUCTION: It is estimated that around 50% of cancer patients require Radiotherapy (RT) at some point during their treatment, hence Therapeutic Radiographers/Radiation Therapists (TR/RTTs) have a key role to play in patient management. It is essen...

A multi-birth metric learning framework based on binary constraints.

Neural networks : the official journal of the International Neural Network Society
Multi-metric learning plays a significant role in improving the generalization of algorithms related to distance metrics since using a single metric is sometimes insufficient to handle complex data. Metric learning can adjust automatically the distan...