AI Medical Compendium Journal:
Nature biomedical engineering

Showing 21 to 30 of 74 articles

An implantable soft robotic ventilator augments inspiration in a pig model of respiratory insufficiency.

Nature biomedical engineering
Severe diaphragm dysfunction can lead to respiratory failure and to the need for permanent mechanical ventilation. Yet permanent tethering to a mechanical ventilator through the mouth or via tracheostomy can hinder a patient's speech, swallowing abil...

Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens.

Nature biomedical engineering
Multiplexed immunofluorescence imaging allows the multidimensional molecular profiling of cellular environments at subcellular resolution. However, identifying and characterizing disease-relevant microenvironments from these rich datasets is challeng...

Graph representation learning in biomedicine and healthcare.

Nature biomedical engineering
Networks-or graphs-are universal descriptors of systems of interacting elements. In biomedicine and healthcare, they can represent, for example, molecular interactions, signalling pathways, disease co-morbidities or healthcare systems. In this Perspe...

Fast and scalable search of whole-slide images via self-supervised deep learning.

Nature biomedical engineering
The adoption of digital pathology has enabled the curation of large repositories of gigapixel whole-slide images (WSIs). Computationally identifying WSIs with similar morphologic features within large repositories without requiring supervised trainin...

A soft robotic sleeve mimicking the haemodynamics and biomechanics of left ventricular pressure overload and aortic stenosis.

Nature biomedical engineering
Preclinical models of aortic stenosis can induce left ventricular pressure overload and coarsely control the severity of aortic constriction. However, they do not recapitulate the haemodynamics and flow patterns associated with the disease. Here we r...

Label-free intraoperative histology of bone tissue via deep-learning-assisted ultraviolet photoacoustic microscopy.

Nature biomedical engineering
Obtaining frozen sections of bone tissue for intraoperative examination is challenging. To identify the bony edge of resection, orthopaedic oncologists therefore rely on pre-operative X-ray computed tomography or magnetic resonance imaging. However, ...

Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning.

Nature biomedical engineering
In tasks involving the interpretation of medical images, suitably trained machine-learning models often exceed the performance of medical experts. Yet such a high-level of performance typically requires that the models be trained with relevant datase...

Self-supervised learning in medicine and healthcare.

Nature biomedical engineering
The development of medical applications of machine learning has required manual annotation of data, often by medical experts. Yet, the availability of large-scale unannotated data provides opportunities for the development of better machine-learning ...

Shifting machine learning for healthcare from development to deployment and from models to data.

Nature biomedical engineering
In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements in clinical capabilities and access to care. This progress has emphasized that, from model developme...

A cost-aware framework for the development of AI models for healthcare applications.

Nature biomedical engineering
Accurate artificial intelligence (AI) for disease diagnosis could lower healthcare workloads. However, when time or financial resources for gathering input data are limited, as in emergency and critical-care medicine, developing accurate AI models, w...