AIMC Topic: Data Accuracy
Clear Filters Showing 51 to 60 of 180 articles
The human-in-the-loop: an evaluation of pathologists' interaction with artificial intelligence in clinical practice.
Histopathology
May 30, 2021
AIMS: One of the major drivers of the adoption of digital pathology in clinical practice is the possibility of introducing digital image analysis (DIA) to assist with diagnostic tasks. This offers potential increases in accuracy, reproducibility, and...
Reproducibility of Results
Breast Neoplasms
Biomarkers, Tumor
Diagnosis, Computer-Assisted
Artificial Intelligence
Research Design
Retrospective Studies
Immunohistochemistry
Calibration
Ki-67 Antigen
Pathology, Clinical
Image Processing, Computer-Assisted
Pathologists
Data Accuracy
Observer Variation
Humans
Explaining deep neural networks for knowledge discovery in electrocardiogram analysis.
Scientific reports
May 26, 2021
Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction...
Converging global crises are forcing the rapid adoption of disruptive changes in drug discovery.
Drug discovery today
May 18, 2021
Spiralling research costs combined with urgent pressures from the Coronavirus 2019 (COVID-19) pandemic and the consequences of climate disruption are forcing changes in drug discovery. Increasing the predictive power of in vitro human assays and usin...
Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 30, 2021
BACKGROUND: Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses i...
Cheetah: A Computational Toolkit for Cybergenetic Control.
ACS synthetic biology
Apr 27, 2021
Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups ...
A primer on applying AI synergistically with domain expertise to oncology.
Biochimica et biophysica acta. Reviews on cancer
Apr 24, 2021
BACKGROUND: The concurrent growth of large-scale oncology data alongside the computational methods with which to analyze and model it has created a promising environment for revolutionizing cancer diagnosis, treatment, prevention, and drug discovery....
Automated system for diagnosing endometrial cancer by adopting deep-learning technology in hysteroscopy.
PloS one
Mar 31, 2021
Endometrial cancer is a ubiquitous gynecological disease with increasing global incidence. Therefore, despite the lack of an established screening technique to date, early diagnosis of endometrial cancer assumes critical importance. This paper presen...
KG2Vec: A node2vec-based vectorization model for knowledge graph.
PloS one
Mar 30, 2021
Since the word2vec model was proposed, many researchers have vectorized the data in the research field based on it. In the field of social network, the Node2Vec model improved on the basis of word2vec can vectorize nodes and edges in social networks,...
A novel method for clinical risk prediction with low-quality data.
Artificial intelligence in medicine
Mar 17, 2021
In real-world data, predictive models for clinical risks (such as adverse drug reactions, hospital readmission, and chronic disease onset) are constantly struggling with low-quality issues, namely redundant and highly correlated features, extreme cat...
Deep learning dose prediction for IMRT of esophageal cancer: The effect of data quality and quantity on model performance.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Mar 10, 2021
PURPOSE: To investigate the effect of data quality and quantity on the performance of deep learning (DL) models, for dose prediction of intensity-modulated radiotherapy (IMRT) of esophageal cancer.
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823