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1.
Lancet Diabetes Endocrinol ; 12(8): 569-595, 2024 Aug.
Article in English | MEDLINE | ID: mdl-39054035

ABSTRACT

Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for complex presentations. However, the rapid advancement of AI also introduces challenges such as potential biases, ethical considerations, and implementation challenges in ensuring that its deployment is equitable. Ensuring inclusive and ethical developments of AI technology can empower both health-care providers and people with diabetes in managing the condition. In this Review, we explore and summarise the current and future prospects of AI across the diabetes care continuum, from enhancing screening and diagnosis to optimising treatment and predicting and managing complications.


Subject(s)
Artificial Intelligence , Diabetes Mellitus , Humans , Artificial Intelligence/trends , Diabetes Mellitus/therapy , Diabetes Mellitus/diagnosis
2.
Health Informatics J ; 30(3): 14604582241267792, 2024.
Article in English | MEDLINE | ID: mdl-39056109

ABSTRACT

Objective: This article aims to describe the implementation of a new health information technology system called Health Connect that is harmonizing cancer data in the Canadian province of Newfoundland and Labrador; explain high-level technical details of this technology; provide concrete examples of how this technology is helping to improve cancer care in the province, and to discuss its future expansion and implications. Methods: We give a technical description of the Health Connect architecture, how it integrated numerous data sources into a single, scalable health information system for cancer data and highlight its artificial intelligence and analytics capacity. Results: We illustrated two practical achievements of Health Connect. First, an analytical dashboard that was used to pinpoint variations in colon cancer screening uptake in small defined geographic regions of the province; and second, a natural language processing algorithm that provided AI-assisted decision support in interpreting appropriate follow-up action based on assessments of breast mammography reports. Conclusion: Health Connect is a cutting-edge, health systems solution for harmonizing cancer screening data for practical decision-making. The long term goal is to integrate all cancer care data holdings into Health Connect to build a comprehensive health information system for cancer care in the province.


Subject(s)
Neoplasms , Humans , Newfoundland and Labrador , Female , Artificial Intelligence/trends , Medical Informatics/methods , Early Detection of Cancer/methods
3.
Article in English | MEDLINE | ID: mdl-39008641

ABSTRACT

Over the past period different reports related to the artificial intelligence (AI) and machine learning used in everyday life have been growing intensely. However, the AI in our country is still very limited, especially in the field of medicine. The aim of this article is to give some review about AI in medicine and the related fields based on published articles in PubMed and Psych Net. A research showed more than 9 thousand articles available at the mentioned databases. After providing some historical data, different AI applications in different fields of medicine are discussed. Finally, some limitations and ethical implications are discussed.


Subject(s)
Artificial Intelligence , Humans , Artificial Intelligence/trends , Machine Learning
5.
Clin Transl Sci ; 17(7): e13897, 2024 Jul.
Article in English | MEDLINE | ID: mdl-39039704

ABSTRACT

Today's approach to medicine requires extensive trial and error to determine the proper treatment path for each patient. While many fields have benefited from technological breakthroughs in computer science, such as artificial intelligence (AI), the task of developing effective treatments is actually getting slower and more costly. With the increased availability of rich historical datasets from previous clinical trials and real-world data sources, one can leverage AI models to create holistic forecasts of future health outcomes for an individual patient in the form of an AI-generated digital twin. This could support the rapid evaluation of intervention strategies in silico and could eventually be implemented in clinical practice to make personalized medicine a reality. In this work, we focus on uses for AI-generated digital twins of clinical trial participants and contend that the regulatory outlook for this technology within drug development makes it an ideal setting for the safe application of AI-generated digital twins in healthcare. With continued research and growing regulatory acceptance, this path will serve to increase trust in this technology and provide momentum for the widespread adoption of AI-generated digital twins in clinical practice.


Subject(s)
Artificial Intelligence , Clinical Trials as Topic , Precision Medicine , Humans , Artificial Intelligence/trends , Precision Medicine/methods , Drug Development/methods
16.
Cell Syst ; 15(6): 483-487, 2024 Jun 19.
Article in English | MEDLINE | ID: mdl-38901402

ABSTRACT

This Voices piece will highlight the impact of artificial intelligence on algorithm development among computational biologists. How has worldwide focus on AI changed the path of research in computational biology? What is the impact on the algorithmic biology research community?


Subject(s)
Algorithms , Artificial Intelligence , Computational Biology , Artificial Intelligence/trends , Computational Biology/methods , Humans
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