AIMC Topic: Referral and Consultation

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A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice.

Medical science monitor : international medical journal of experimental and clinical research
Ophthalmology is undergoing rapid transformation through the integration of smart technologies such as artificial intelligence (AI), big data analytics, and clinical decision support systems (CDSS). With increasing pressure to improve clinical effici...

AI assisted triage of UK patients in mental health care services: a qualitative focus group study of patients' attitudes.

BMC psychiatry
BACKGROUND: The referral process between healthcare services can be complex, especially in psychiatry, leading to significant delays and 'hidden waiting lists'. Digital approaches may be helpful. The CHRONOSIG (CHRONOlogical SIGnature) project aims t...

AI-MDT: an automatic and intelligent multidisciplinary team consultations platform for lung cancer diagnosis.

Journal of cancer research and clinical oncology
PURPOSE: Multidisciplinary team (MDT) consultations are crucial for managing pulmonary nodules, yet face challenges in efficiency, evidence-based decision support, and data utilization within the MDT process. We present an integrated artificial intel...

Artificial intelligence for early palliative referral in adult oncology: opportunities, challenges and future directions.

BMJ supportive & palliative care
BACKGROUND: In oncology, early palliative care enhances quality of life and may increase survival; yet, because of resource limitations and overestimation of prognosis, referrals frequently happen late. Due to a shortage of specialised workers, this ...

Leveraging Artificial Intelligence to Enhance Screening, Brief Intervention, and Referral to Treatment Training for Psychiatric Mental Health Nurse Practitioner Students: A Case Study and Future Directions for Virtual Reality Integration.

Journal of doctoral nursing practice
Psychiatric mental health nurse practitioners (PMHNPs) play a vital role in addressing substance use disorders, particularly in underserved regions. This article aimed to explore the effectiveness of artificial intelligence (AI)-generated Screening...

An approach to make general practitioner referrals suitable for artificial intelligence deployment.

The New Zealand medical journal
Outpatient referrals for hospital specialist assessment are an increasing workload that carry significant risk if not attended to in a timely manner. This viewpoint discusses how decision support (including artificial intelligence and machine learnin...

Digital Information Sharing Before Consultations in General Practice: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: Digital tools that enable patients to submit information before consultations, such as Accurx and eConsult, are increasingly used in general practice. These systems aim to streamline workflows, improve documentation, and optimize consulta...

Layperson-Friendly AI Translation of Medical Documents to Improve Doctor-Patient Communication: Protocols for the AI-INFOCARE and AI-MEDTALK Randomized Controlled Trials.

JMIR research protocols
BACKGROUND: Many patients struggle to understand referral letters and discharge summaries; low health literacy is prevalent, and short consultations limit explanations. Large language models (LLMs) can translate clinical jargon into layperson languag...

AI-generated neurology consultation summaries improve efficiency and reduce documentation burden in the emergency department.

Scientific reports
Physicians face a significant documentation burden, spending twice as much time on electronic health records (EHRs) as on direct patient care. Consultation summary reports from the emergency department (ED) are critical for continuity of care and cli...