Future-ai:International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

Endovascular repair of symptomatic abdominal aortic aneurysm: a seminal case in West Africa

Abdominal aortic aneurysm (AAA) is a fatal disease with high perioperative morbidity and mortality. Endovascular AAA repair (EVAR) is associated with remarkable improvement in the morbidity, mortality and length of hospital stay relative to open operative repair. We report a 79-year-old man with epigastric pain, which was diagnosed to be due to AAA on a computerised tomography angiogram (CTA). His only risk factor was hypertension. He had endovascular repair in 2018, the first-ever in Ghana and West Africa. 2021 is the 3rd year of surveillance post- EVAR with no disease progression or complication. This seminal case is a beacon of hope in Ghana’s resource-constrained healthcare system

Follicular thyroid carcinoma with internal jugular vein tumour thrombus

Tumour thrombus is the presence of tumour cells in great vessels. The reported incidence of tumour thrombus in thyroid carcinoma is about 0.2-3.8%. Being asymptomatic, detection of tumour thrombosis clinically is difficult. We present the report of internal jugular vein (IJV) tumour thrombosis in a known follicular thyroid carcinoma patient, detected with multimodality imaging. Grayscale ultrasound scan of the neck showed a well-defined, bi-lobed (2.4 x 1.5) cm, intraluminal solid lesion with homogeneous echotexture within the distal left IJV close to its confluence with the ipsilateral subclavian vein. The lesion showed significant internal vascularity on colour Doppler assessment. The sonographic findings confirmed further imaging with computed tomography (CT) and radioisotope scans. We con-clude that patients with thyroid cancer should be evaluated for tumour thrombosis both clinically and with imaging, particularly with ultrasound and CT/MRI or nuclear medicine, as it has prognostic implications