Revolutionizing healthcare: the role of artificial intelligence in clinical practice
Introduction Healthcare systems are complex and challenging for all stakeholders, but
artificial intelligence (AI) has transformed various fields, including healthcare, with the …
artificial intelligence (AI) has transformed various fields, including healthcare, with the …
Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …
potential for many fields—including medicine—to benefit from the insights that AI techniques …
FAT-Net: Feature adaptive transformers for automated skin lesion segmentation
Skin lesion segmentation from dermoscopic image is essential for improving the quantitative
analysis of melanoma. However, it is still a challenging task due to the large scale variations …
analysis of melanoma. However, it is still a challenging task due to the large scale variations …
Disparities in dermatology AI performance on a diverse, curated clinical image set
R Daneshjou, K Vodrahalli, RA Novoa, M Jenkins… - Science …, 2022 - science.org
An estimated 3 billion people lack access to dermatological care globally. Artificial
intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However …
intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However …
Deep learning in cancer pathology: a new generation of clinical biomarkers
Clinical workflows in oncology rely on predictive and prognostic molecular biomarkers.
However, the growing number of these complex biomarkers tends to increase the cost and …
However, the growing number of these complex biomarkers tends to increase the cost and …
Lack of transparency and potential bias in artificial intelligence data sets and algorithms: a scoping review
R Daneshjou, MP Smith, MD Sun… - JAMA …, 2021 - jamanetwork.com
Importance Clinical artificial intelligence (AI) algorithms have the potential to improve clinical
care, but fair, generalizable algorithms depend on the clinical data on which they are trained …
care, but fair, generalizable algorithms depend on the clinical data on which they are trained …
[HTML][HTML] Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts
Background Multiple studies have compared the performance of artificial intelligence (AI)–
based models for automated skin cancer classification to human experts, thus setting the …
based models for automated skin cancer classification to human experts, thus setting the …
Human–computer collaboration for skin cancer recognition
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial
intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI …
intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI …
Key challenges for delivering clinical impact with artificial intelligence
Background Artificial intelligence (AI) research in healthcare is accelerating rapidly, with
potential applications being demonstrated across various domains of medicine. However …
potential applications being demonstrated across various domains of medicine. However …
Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review
OT Jones, RN Matin, M Van der Schaar… - The Lancet Digital …, 2022 - thelancet.com
Skin cancers occur commonly worldwide. The prognosis and disease burden are highly
dependent on the cancer type and disease stage at diagnosis. We systematically reviewed …
dependent on the cancer type and disease stage at diagnosis. We systematically reviewed …