AIMC Topic: Diagnostic Tests, Routine

Clear Filters Showing 51 to 60 of 80 articles

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 ...

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 ...

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...

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...

Artificial intelligence-based decision-making for age-related macular degeneration.

Theranostics
Artificial intelligence (AI) based on convolutional neural networks (CNNs) has a great potential to enhance medical workflow and improve health care quality. Of particular interest is practical implementation of such AI-based software as a cloud-base...

Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI.

Journal of magnetic resonance imaging : JMRI
Deep learning is a branch of artificial intelligence where networks of simple interconnected units are used to extract patterns from data in order to solve complex problems. Deep-learning algorithms have shown groundbreaking performance in a variety ...

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...

Assessment of Functional Phosphatidylinositol 3-Kinase Pathway Activity in Cancer Tissue Using Forkhead Box-O Target Gene Expression in a Knowledge-Based Computational Model.

The American journal of pathology
The phosphatidylinositol 3-kinase (PI3K) pathway is commonly activated in cancer. Tumors are potentially sensitive to PI3K pathway inhibitors, but reliable diagnostic tests that assess functional PI3K activity are lacking. Because PI3K pathway activi...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Scientific reports
Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The objective of this study was to develop and validate a multi-parameterized artificial neural network ...