AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Diagnostic Tests, Routine

Showing 51 to 60 of 73 articles

Clear Filters

Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Poor electronic medical record (EMR) usability is detrimental to both clinicians and patients. A better EMR would provide concise, context sensitive patient data, but doing so entails the difficult task of knowing which data are relevant. To determin...

Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification.

Integrative biology : quantitative biosciences from nano to macro
Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and prov...

The Big Picture on the "AI Turn" for Digital Health: The Internet of Things and Cyber-Physical Systems.

Omics : a journal of integrative biology
This article offers an analysis of the ways in which digital health innovations are being coproduced by mainstreaming of artificial intelligence (AI), the Internet of Things (IoT), and cyber-physical systems (CPS) in health care. CPS blurs the bounda...

Whole-brain death and integration: realigning the ontological concept with clinical diagnostic tests.

Theoretical medicine and bioethics
For decades, physicians, philosophers, theologians, lawyers, and the public considered brain death a settled issue. However, a series of recent cases in which individuals were declared brain dead yet physiologically maintained for prolonged periods o...

Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Emergency departments (EDs) continue to pursue optimal patient flow without sacrificing quality of care. The speed with which a healthcare provider receives pertinent information, such as results from clinical orders, can impact flow. We s...

A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: In classification and diagnostic testing, the receiver-operator characteristic (ROC) plot and the area under the ROC curve (AUC) describe how an adjustable threshold causes changes in two types of error: false positives and false negative...

In vivo imaging of phosphocreatine with artificial neural networks.

Nature communications
Phosphocreatine (PCr) plays a vital role in neuron and myocyte energy homeostasis. Currently, there are no routine diagnostic tests to noninvasively map PCr distribution with clinically relevant spatial resolution and scan time. Here, we demonstrate ...

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches.

International journal of molecular sciences
Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection ...