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Delivery of Health Care

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Smart data-driven medical decisions through collective and individual anomaly detection in healthcare time series.

International journal of medical informatics
BACKGROUND: Anomalies in healthcare refer to deviation from the norm of unusual or unexpected patterns or activities related to patients, diseases or medical centres. Detecting these anomalies is crucial for timely interventions and efficient decisio...

Assessing Yemeni university students' public perceptions toward the use of artificial intelligence in healthcare.

Scientific reports
Artificial intelligence (AI) integration in healthcare has emerged as a transformative force, promising to enhance medical diagnosis, treatment, and overall healthcare delivery. Hence, this study investigates university students' perceptions of using...

Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine.

Journal of general internal medicine
Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended conse...

Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model.

Scientific reports
Cancer is a life-threatening disease resulting from a genetic disorder and a range of metabolic anomalies. In particular, lung and colon cancer (LCC) are among the major causes of death and disease in humans. The histopathological diagnoses are criti...

Developing healthcare language model embedding spaces.

Artificial intelligence in medicine
Pre-trained Large Language Models (LLMs) have revolutionised Natural Language Processing (NLP) tasks, but often struggle when applied to specialised domains such as healthcare. The traditional approach of pre-training on large datasets followed by ta...

Artificial intelligence governance framework for healthcare.

Healthcare management forum
Recent advancements in the field of Artificial Intelligence (AI) provide promising applications of this technology with the aim of solving complex healthcare challenges. These include optimizing operational efficiencies, supporting clinical administr...

Adversarial Examples on XAI-Enabled DT for Smart Healthcare Systems.

Sensors (Basel, Switzerland)
There have recently been rapid developments in smart healthcare systems, such as precision diagnosis, smart diet management, and drug discovery. These systems require the integration of the Internet of Things (IoT) for data acquisition, Digital Twins...

Laboratory Data as a Potential Source of Bias in Healthcare Artificial Intelligence and Machine Learning Models.

Annals of laboratory medicine
Artificial intelligence (AI) and machine learning (ML) are anticipated to transform the practice of medicine. As one of the largest sources of digital data in healthcare, laboratory results can strongly influence AI and ML algorithms that require lar...

A look at the emerging trends of large language models in ophthalmology.

Current opinion in ophthalmology
PURPOSE OF REVIEW: As the surge in large language models (LLMs) and generative artificial intelligence (AI) applications in ophthalmology continue to expand, this review seeks to update physicians of the current progress, to catalyze further work to ...

The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems.

Health systems and reform
Mobile health has the potential to revolutionize health care delivery and patient engagement. In this work, we discuss how integrating Artificial Intelligence into digital health applications focused on supply chain operation, patient management, and...