New machine-learning technologies for computer-aided diagnosis.

TL;DR: It is argued that AI’s scope and depth of research need to be expanded to achieve ground-breaking progress in precision oncology.

TL;DR: In this article , the authors summarize recent progress in mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms.

TL;DR: In this paper , the authors proposed an end-to-end multi-modal graph learning framework (MMGL) for disease prediction with multidimensional medical data, where the latent graph structure is captured through an effective way of adaptive graph learning.

TL;DR: NeuroXAI as mentioned in this paper is a framework for explainable deep learning networks to increase the trust of medical experts, which can be used to assist radiologists and medical professionals in the detection and diagnosis of brain tumors in the clinical routine of cancer patients.

TL;DR: An algorithm based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy and diabetic macular edema in retinal fundus photographs from adults with diabetes.

TL;DR: Genes implicated in DLBCL outcome included some that regulate responses to B-cell–receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis, and identify rational targets for intervention.

TL;DR: A novel deep learning architecture performs device-independent tissue segmentation of clinical 3D retinal images followed by separate diagnostic classification that meets or exceeds human expert clinical diagnoses of retinal disease.

TL;DR: A machine-learning algorithm is devised that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in an 800-person cohort and shows that it accurately predicts personalized postprandial glycemic response to real-life meals, and a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postpr andial responses and consistent alterations to gut microbiota configuration.