AIMC Topic:
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Machine Learning Models for Analysis of Vital Signs Dynamics: A Case for Sepsis Onset Prediction.
Journal of healthcare engineering
Nov 3, 2019
OBJECTIVE: Achieving accurate prediction of sepsis detection moment based on bedside monitor data in the intensive care unit (ICU). A good clinical outcome is more probable when onset is suspected and treated on time, thus early insight of sepsis ons...
Early Diagnosis
Analysis of Variance
Vital Signs
Support Vector Machine
Intensive Care Units
Humans
Area Under Curve
Female
Models, Biological
Case-Control Studies
Aged
Diagnosis, Computer-Assisted
Aged, 80 and over
Young Adult
Sepsis
Adult
Machine Learning
Adolescent
Male
Software
Middle Aged
Algorithms
System-level responses to cisplatin in pro-apoptotic stages of breast cancer MCF-7 cell line.
Computational biology and chemistry
Nov 2, 2019
Cisplatin ceases cell division and induces apoptosis in cancer cell lines. It is well established that cisplatin alters the expression of many genes involved in several cellular processes and pathways including transcription, p53 signaling pathway, a...
Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers.
Computational and mathematical methods in medicine
Nov 2, 2019
As a large amount of genetic data are accumulated, an effective analytical method and a significant interpretation are required. Recently, various methods of machine learning have emerged to process genetic data. In addition, machine learning analysi...
Same-day antimicrobial susceptibility test using acoustic-enhanced flow cytometry visualized with supervised machine learning.
Journal of medical microbiology
Oct 30, 2019
Antimicrobial susceptibility is slow to determine, taking several days to fully impact treatment. This proof-of-concept study assessed the feasibility of using machine-learning techniques for analysis of data produced by the flow cytometer-assisted ...
Artificial Intelligence in Radiology: A Call for Thoughtful Application.
Clinical and translational science
Oct 30, 2019
[Development and national rollout of electronic decision support systems using artificial intelligence in the field of onco-hematology].
Magyar onkologia
Oct 30, 2019
Systematic, structured and longitudinal collection of realtime Big Patient Data and the analysis of aggregated diagnostic, therapeutic and therapy response data of onco-hematologic patients leads to the development of nationwide dynamic disease regis...
Proof of Concept of an Assistive Robotic Arm Control Using Artificial Stereovision and Eye-Tracking.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 30, 2019
Assistive robotic arms have become popular to help users with upper limb disabilities achieve autonomy in their daily tasks, such as drinking and grasping objects in general. Usually, these robotic arms are controlled with an adapted joystick. Joysti...
ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results.
Journal of chemical information and modeling
Oct 25, 2019
Tuberculosis remains one of the deadliest infectious diseases worldwide. Only 5-15% of people infected with develop active TB disease (ATB), while others remain latently infected (LTBI) during their lifetime, which has a completely different clinica...
Novel Consensus Architecture To Improve Performance of Large-Scale Multitask Deep Learning QSAR Models.
Journal of chemical information and modeling
Oct 25, 2019
Advances in the development of high-throughput screening and automated chemistry have rapidly accelerated the production of chemical and biological data, much of them freely accessible through literature aggregator services such as ChEMBL and PubChem...
A database for using machine learning and data mining techniques for coronary artery disease diagnosis.
Scientific data
Oct 23, 2019
We present the coronary artery disease (CAD) database, a comprehensive resource, comprising 126 papers and 68 datasets relevant to CAD diagnosis, extracted from the scientific literature from 1992 and 2018. These data were collected to help advance r...
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