[HTML][HTML] The intersection of ChatGPT, clinical medicine, and medical education

RSY Wong, LC Ming, RAR Ali - JMIR Medical Education, 2023 - mededu.jmir.org
As we progress deeper into the digital age, the robust development and application of
advanced artificial intelligence (AI) technology, specifically generative language models like …

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

W Lotter, MJ Hassett, N Schultz, KL Kehl, EM Van Allen… - Cancer Discovery, 2024 - AACR
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: what can they learn from each other?

J Mökander, P Juneja, DS Watson, L Floridi - Minds and Machines, 2022 - Springer
On the whole, the US Algorithmic Accountability Act of 2022 (US AAA) is a pragmatic
approach to balancing the benefits and risks of automated decision systems. Yet there is still …

[HTML][HTML] A medical ethics framework for conversational artificial intelligence

E Fournier-Tombs, J McHardy - Journal of Medical Internet Research, 2023 - jmir.org
The launch of OpenAI's GPT-3 model in June 2020 began a new era for conversational
chatbots. While there are chatbots that do not use artificial intelligence (AI), conversational …

[HTML][HTML] Stuck in translation: Stakeholder perspectives on impediments to responsible digital health

C Landers, E Vayena, J Amann… - Frontiers in Digital …, 2023 - frontiersin.org
Spurred by recent advances in machine learning and electronic hardware, digital health
promises to profoundly transform medicine. At the same time, however, it raises conspicuous …

Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology

A Signoroni, A Ferrari, S Lombardi, M Savardi… - Nature …, 2023 - nature.com
Abstract Full Laboratory Automation is revolutionizing work habits in an increasing number
of clinical microbiology facilities worldwide, generating huge streams of digital images for …

Prediction of complications and prognostication in perioperative medicine: a systematic review and PROBAST assessment of machine learning tools

P Arina, MR Kaczorek, DA Hofmaenner… - …, 2024 - pubs.asahq.org
Background The utilization of artificial intelligence and machine learning as diagnostic and
predictive tools in perioperative medicine holds great promise. Indeed, many studies have …

Lifelong nnU-Net: a framework for standardized medical continual learning

C González, A Ranem, D Pinto dos Santos… - Scientific Reports, 2023 - nature.com
As the enthusiasm surrounding Deep Learning grows, both medical practitioners and
regulatory bodies are exploring ways to safely introduce image segmentation in clinical …

A review of the technology, training, and assessment methods for the first real-time AI-enhanced medical device for endoscopy

A Cherubini, NN Dinh - Bioengineering, 2023 - mdpi.com
Artificial intelligence (AI) has the potential to assist in endoscopy and improve decision
making, particularly in situations where humans may make inconsistent judgments. The …

Interpretable artificial intelligence in radiology and radiation oncology

S Cui, A Traverso, D Niraula, J Zou… - The British Journal of …, 2023 - academic.oup.com
Artificial intelligence has been introduced to clinical practice, especially radiology and
radiation oncology, from image segmentation, diagnosis, treatment planning and prognosis …