Cancer Genetics, Journal Year: 2024, Volume and Issue: 290-291, P. 56 - 60
Published: Dec. 22, 2024
Language: Английский
Cureus, Journal Year: 2024, Volume and Issue: unknown
Published: June 15, 2024
Artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing health care by offering unprecedented opportunities to enhance patient care, optimize clinical workflows, advance medical research. However, the integration of AI ML into healthcare systems raises significant ethical considerations that must be carefully addressed ensure responsible equitable deployment. This comprehensive review explored multifaceted surrounding use in including privacy data security, algorithmic bias, transparency, validation, professional responsibility. By critically examining these dimensions, stakeholders can navigate complexities while safeguarding welfare upholding principles. embracing best practices fostering collaboration across interdisciplinary teams, community harness full potential usher a new era personalized data-driven prioritizes well-being equity.
Language: Английский
Citations
44
Nature Medicine, Journal Year: 2024, Volume and Issue: 30(10), P. 2977 - 2989
Published: July 4, 2024
Abstract Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses broad array data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations multimodal neuroimaging, identify the etiologies contributing individuals. The study, drawing on 51,269 participants 9 independent, geographically diverse datasets, facilitated identification 10 distinct etiologies. It aligns diagnoses with similar strategies, ensuring robust predictions even incomplete data. Our achieved microaveraged area under receiver operating characteristic curve (AUROC) 0.94 classifying individuals normal cognition, mild cognitive impairment dementia. Also, AUROC was 0.96 differentiating demonstrated proficiency addressing mixed cases, mean 0.78 two co-occurring pathologies. In randomly selected subset 100 neurologist assessments augmented by our AI exceeded neurologist-only 26.25%. Furthermore, aligned biomarker evidence its associations different proteinopathies were substantiated through postmortem findings. framework has potential be integrated as screening tool clinical settings drug trials. Further prospective studies are needed confirm ability improve patient care.
Language: Английский
Citations
21
Springer eBooks, Journal Year: 2023, Volume and Issue: unknown, P. 1 - 38
Published: Jan. 1, 2023
Language: Английский
Citations
35
Springer eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 1461 - 1498
Published: Jan. 1, 2024
Language: Английский
Citations
13
AIP conference proceedings, Journal Year: 2025, Volume and Issue: 3262, P. 020020 - 020020
Published: Jan. 1, 2025
Citations
1
Advances in pharmacology, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 1, 2025
Language: Английский
Citations
0
Artificial Intelligence in Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 103116 - 103116
Published: April 1, 2025
Language: Английский
Citations
0
Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 27 - 74
Published: March 7, 2025
The application of artificial intelligence in the design and conduct patient recruitment clinical trials is targeted at addressing some key inefficiencies, including longer timelines lack participant characteristics. This chapter presents readers with opportunities advantages using AI to make protocols more specific execute efficiently. integrates thorough discussions that explain how predictive analytics, machine learning, other tools such as natural language processing can be used identify participants refine trials. Moreover, this contains a description use results implementation help provided case studies. In way, it possible learn increase efficiency trial, number sourced participants, issues technology. Ethical regulatory are also discussed chapter, which provides an overview role functions play process
Language: Английский
Citations
0
medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: Feb. 11, 2024
Abstract Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses broad array data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, multimodal neuroimaging, identify the etiologies contributing individuals. The study, drawing on 51, 269 participants 9 independent, geographically diverse datasets, facilitated identification 10 distinct etiologies. It aligns diagnoses with similar strategies, ensuring robust predictions even incomplete data. Our achieved micro-averaged area under receiver operating characteristic curve (AUROC) 0.94 classifying individuals normal cognition, mild cognitive impairment dementia. Also, AUROC was 0.96 differentiating demonstrated proficiency addressing mixed cases, mean 0.78 two cooccurring pathologies. In randomly selected subset 100 neurologist assessments augmented by our exceeded neurologist-only evaluations 26.25%. Furthermore, aligned biomarker evidence its associations different proteinopathies were substantiated through postmortem findings. framework has potential be integrated as screening tool various clinical settings drug trials, promising implications person-level management.
Language: Английский
Citations
3
Muscle & Nerve, Journal Year: 2023, Volume and Issue: 69(3), P. 260 - 272
Published: Dec. 27, 2023
Abstract The rapid advancements in artificial intelligence (AI), including machine learning (ML), and deep (DL) have ushered a new era of technological breakthroughs healthcare. These technologies are revolutionizing the way we utilize medical data, enabling improved disease classification, more precise diagnoses, better treatment selection, therapeutic monitoring, highly accurate prognostication. Different ML DL models been used to distinguish between electromyography signals normal individuals those with amyotrophic lateral sclerosis myopathy, accuracy ranging from 67% 99.5%. also successfully applied neuromuscular ultrasound, use segmentation techniques achieving diagnostic at least 90% for nerve entrapment disorders, 87% inflammatory myopathies. Other successful AI applications include prediction response, prognostication intensive care unit admissions patients myasthenia gravis. Despite these remarkable strides, significant knowledge, attitude, practice gaps persist, within field electrodiagnostic medicine. In this narrative review, highlight fundamental principles draw parallels intricacies human brain networks. Specifically, explore immense potential that holds studies, other aspects While there exciting possibilities future, it is essential acknowledge understand limitations take proactive steps mitigate challenges. This collective endeavor advancement healthcare through strategic responsible integration technologies.
Language: Английский
Citations
9