AIMC Topic: Benchmarking
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WHO and ITU establish benchmarking process for artificial intelligence in health.
Lancet (London, England)
Mar 29, 2019
GuacaMol: Benchmarking Models for de Novo Molecular Design.
Journal of chemical information and modeling
Mar 19, 2019
De novo design seeks to generate molecules with required property profiles by virtual design-make-test cycles. With the emergence of deep learning and neural generative models in many application areas, models for molecular design based on neural net...
netDx: interpretable patient classification using integrated patient similarity networks.
Molecular systems biology
Mar 14, 2019
Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse da...
In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening.
Journal of chemical information and modeling
Mar 5, 2019
Reports of successful applications of machine learning (ML) methods in structure-based virtual screening (SBVS) are increasing. ML methods such as convolutional neural networks show promising results and often outperform traditional methods such as e...
Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric Evaluation.
International journal of radiation oncology, biology, physics
Mar 2, 2019
PURPOSE: Organ-at-risk (OAR) delineation is a key step in treatment planning but can be time consuming, resource intensive, subject to variability, and dependent on anatomical knowledge. We studied deep learning (DL) for automated delineation of mult...
The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice.
Seminars in cutaneous medicine and surgery
Mar 1, 2019
In the past decade, machine learning and artificial intelligence have made significant advancements in pattern analysis, including speech and natural language processing, image recognition, object detection, facial recognition, and action categorizat...
Benchmarking machine learning methods for comprehensive chemical fingerprinting and pattern recognition.
Journal of chromatography. A
Feb 23, 2019
Machine learning (ML) has been used previously to recognize particular patterns of constituent compounds. Here, ML is used with comprehensive chemical fingerprints that capture the distribution of all constituent compounds to flexibly perform various...
Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark.
European journal of cancer (Oxford, England : 1990)
Feb 22, 2019
BACKGROUND: Several recent publications have demonstrated the use of convolutional neural networks to classify images of melanoma at par with board-certified dermatologists. However, the non-availability of a public human benchmark restricts the comp...
Detecting and interpreting myocardial infarction using fully convolutional neural networks.
Physiological measurement
Jan 15, 2019
OBJECTIVE: We aim to provide an algorithm for the detection of myocardial infarction that operates directly on ECG data without any preprocessing and to investigate its decision criteria.
Use of Machine Learning to Identify Follow-Up Recommendations in Radiology Reports.
Journal of the American College of Radiology : JACR
Dec 29, 2018
PURPOSE: The aims of this study were to assess follow-up recommendations in radiology reports, develop and assess traditional machine learning (TML) and deep learning (DL) models in identifying follow-up, and benchmark them against a natural language...
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