359.866 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Predicting Phospholipidosis Using Machine Learning
…on predictive methods for phospholipidosis showed that state of the art machine learning methods produced the best results. Here we extend this work by looking at a larger data set mined from the literature. We find that circular fingerprints lead to better models than either E-Dragon descriptors…
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Machine Learning in Systems Biology
This supplement contains extended versions of a selected subset of papers presented at the workshop MLSB 2007, Machine Learning in Systems Biology, Evry, France, from September 24 to 25, 2007.
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Artikel Jurnal Teks lengkap
Visible Machine Learning for Biomedicine
A major ambition of artificial intelligence lies in translating patient data to successful therapies. Machine learning models face particular challenges in biomedicine, however, including handling of extreme data heterogeneity and lack of mechanistic insight into predictions. Here, we argue for…
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Machine-learning reprogrammable metasurface imager
…can be trained in-situ to generate the radiation patterns required by machine-learning optimized measurement modes. This imager is electronically reprogrammed in real time to access the optimized solution for an entire data set, realizing storage and transfer of full-resolution raw data in…
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Machine learning and medical education
Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and other products are glimmers of a future in which these tools…
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Machine Learning for Medical Imaging
Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image…
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Machine learning methods in chemoinformatics
Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure–activity relationships (QSAR)…
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An Introduction to Machine Learning
In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever‐increasing amount of data and computational power as well as the discovery of improved learning algorithms. However, the idea of a computer learning some abstract…
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Machine Learning in Breast MRI
Machine-learning techniques have led to remarkable advances in data extraction and analysis of medical imaging. Applications of machine learning to breast MRI continue to expand rapidly as increasingly accurate 3D breast and lesion segmentation allows the combination of radiologist-level…
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Machine learning meets pK (a)
…is trained on a literature compilation of monoprotic compounds. Different machine learning models were tested and random forest performed best given a five-fold cross-validation (mean absolute error=0.682, root mean squared error=1.032, correlation coefficient r (2) =0.82). We test our model on two…
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Machine Learning on Mainstream Microcontrollers †
This paper presents the Edge Learning Machine (ELM), a machine learning framework for edge devices, which manages the training phase on a desktop computer and performs inferences on microcontrollers. The framework implements, in a platform-independent C language, three supervised machine learning…
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Artikel Jurnal Teks lengkap
Interpretable machine learning for genomics
…for humans to understand without the aid of advanced statistical methods. Machine learning (ML) algorithms, which are designed to automatically find patterns in data, are well suited to this task. Yet these models are often so complex as to be opaque, leaving researchers with few clues about…
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