AI also applies to PCa treatment, whether surgical intervention or radiotherapy, skills training, or assessment, to improve treatment modalities and outcome prediction. We should re-define the role of human doctors, and accordingly, medical education should also be altered. For example, a virtual, “half-cheetah”—a stick figure used in mo-, one test but would flail around on the floor. ... discovered potential cancer cures yet failed to distinguish masks from faces. Far from it. Characteristic Latent Features for Analyzing Digital Mental Health Interaction and Improved Explainability, Radiomics machine learning study with a small sample size: single random training-test set split may result in unreliable results, Quantification of Continuous Flood Hazard using Random Forrest Classification and Flood Insurance Claims at Large Spatial Scales: A Pilot Study in Southeast Texas, DOME: Recommendations for supervised machine learning validation in biology, The Application of Artificial Intelligence in Prostate Cancer Management—What Improvements Can Be Expected? Imitation learning from observation (LfO) is more preferable than imitation learning from demonstration (LfD) due to the nonnecessity of expert actions when reconstructing the expert policy from the expert data. A Systematic Review, On the Guaranteed Almost Equivalence between Imitation Learning from Observation and Demonstration, Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data, On the objectivity, reliability, and validity of deep learning enabled bioimage analyses, Transparency and reproducibility in artificial intelligence, Cyberspace and Artificial Intelligence: The New Face of Cyber-Enhanced Hybrid Threats. AI is prevalent in our daily lives we use it in search engines, automated emails, online customized ad campaigns, chat boxes, smart devices, and smartphones. The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. Next, we discuss the different types of reproducibility, and for each one, we discuss its importance, barriers to enforcement, and suggestions to help achieve it. Artificial Intelligence* Reproducibility of Results Just because algorithms are based on code doesn't mean experiments are easily replicated. Last week, at a meeting of the Association for the Advancement of Artificial Intelligence in New Orleans, Louisiana, reproducibility was on the agenda, with some teams diagnosing the problem—and one laying out tools to mitigate it. In the image pre-processing stage, the authors propose an improved geometric feature based face location method to analyze the facial features of human. We identify obstacles hindering transparent and reproducible AI research as faced by McKinney et al and provide solutions with implications for the broader field. AI has the potential to reshape prostate cancer (PCa) management thanks to growing applications in the field. Or it, might be that the code is simply lost, on a, crashed disk or stolen laptop—what Rougier. AI in PCa management has the potential to provide a useful role by predicting PCa more accurately, using a multiomic approach and risk-stratifying patients to provide personalized medicine. Authors Hutson, Matthew 1; 1 Matthew Hutson is a journalist in New York City. A systematic review was performed, based on PubMed MEDLINE, Google Scholar, and DBLP databases for original studies published in English from January 2009 to January 2019 relevant to PCa, AI, Machine Learning, Artificial Neural Networks, Convolutional Neural Networks, and Natural-Language Processing. showed the high potential of artificial intelligence for breast cancer screening. Hence, our findings greatly extend the potential of LfO and suggest that we can safely apply LfO without sacrificing the performance compared to LfD in practice. Published: 19 Feb 2018 learning, in which computers derive exper-, tise from experience, the training data for. Answers to these questions can be easily included in the supplementary material of published papers. Background: Using smartphones and wearable sensor technology has sparked a broad engagement of data science and machine learning methods to leverage the complex, assorted amount of data. Materials and Methods: Two binary tasks with different levels of di culty ('simple' task, glioblastoma [GBM, n=109] vs. brain metastasis [n=58]; 'di cult' task, low-[n=163] vs. high grade [n=95] meningiomas) were performed using radiomics features from magnetic resonance imaging (MRI). Rather, ML, similar to many other disciplines, faces a reproducibility crisis. A total of 1008 articles were reviewed, and 48 articles were included. Rather, ML, similar to many other disciplines, faces a reproducibility crisis. ResearchGate has not been able to resolve any references for this publication. 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