359.866 hasil untuk machine learning
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Forecasting Corn Yield With Machine Learning Ensembles
…to more accurately predict crop yields. Recent research has shown that machine learning (ML) can provide reasonable predictions faster and with higher flexibility compared to simulation crop modeling. However, a single machine learning model can be outperformed by a “committee” of models (machine…
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Practical Vitamin D Supplementation Using Machine Learning
BACKGROUND: Patients with breast cancer are at increased risk of developing osteoporosis. Maintaining normal levels of vitamin D may decrease the risk of osteoporosis, and vitamin D levels must be corrected in patients who develop osteoporosis before beginning bone modifying agents. Therefore, it…
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Data science and machine learning in anesthesiology
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods that are largely inference-based, ML is geared more towards making accurate predictions. ML is a field of artificial intelligence concerned with developing algorithms and models to perform prediction…
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Applications of Machine Learning in Cardiac Electrophysiology
Artificial intelligence through machine learning (ML) methods is becoming prevalent throughout the world, with increasing adoption in healthcare. Improvements in technology have allowed early applications of machine learning to assist physician efficiency and diagnostic accuracy. In…
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Artificial Intelligence, Machine Learning, and Cardiovascular Disease
…recently, with the advent of advances in computing, algorithms enabling machine learning, especially deep learning networks that mimic the human brain in function, there has been renewed interest to use them in clinical medicine. In cardiovascular medicine, AI-based systems have found new…
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Breast Cancer Type Classification Using Machine Learning
…cancer, from non-triple negative breast cancer. Here we propose use of a machine learning (ML) approach for classification of triple negative breast cancer and non-triple negative breast cancer patients using gene expression data. Methods: We performed analysis of RNA-Sequence data from 110 triple…
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Tackling Photonic Inverse Design with Machine Learning
Machine learning, as a study of algorithms that automate prediction and decision‐making based on complex data, has become one of the most effective tools in the study of artificial intelligence. In recent years, scientific communities have been gradually merging data‐driven approaches with…
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Has machine learning rendered simple rules obsolete?
…obsolete with the arrival of artificial intelligence, and in particular machine learning (ML)? Can ML deliver better algorithmic rules than traditional simple legal rules? This paper argues that the answer to these question is “no” by building an argument based on three increasingly more serious…
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Machine learning empowers phosphoproteome prediction in cancers
MOTIVATION: Reversible protein phosphorylation is an essential post-translational modification regulating protein functions and signaling pathways in many cellular processes. Aberrant activation of signaling pathways often contributes to cancer development and progression. The mass…
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Laboratory earthquake forecasting: A machine learning competition
…by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses…
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Machine learning predictivity applied to consumer creditworthiness
…models using a Brazilian bank’s loan database, and exploring machine learning techniques. We develop Support Vector Machine, Decision Trees, Bagging, AdaBoost and Random Forest models, and compare their predictive accuracy with a benchmark based on a Logistic Regression model. Comparisons are…
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DNA-PAINT Imaging Accelerated by Machine Learning
…can be adopted to analyze other SMLM datasets. We anticipate that this machine learning method enables faster and even live-cell DNA-PAINT imaging in the future.
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Machine learning and health need better values
Health care is a human process that generates data from human lives, as well as the care they receive. Machine learning has worked in health to bring new technology into this sociotechnical environment, using data to support a vision of healthier living for everyone. Interdisciplinary fields of…
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Classifying grains using behaviour-informed machine learning
Sorting granular materials such as ores, coffee beans, cereals, gravels and pills is essential for applications in mineral processing, agriculture and waste recycling. Existing sorting methods are based on the detection of contrast in grain properties including size, colour, density and chemical…
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Machine learning for microfluidic design and control
…operation. The intuition of microfluidic experts can be captured through machine learning, where complex statistical models are trained for pattern recognition and subsequently used for event prediction. Integration of machine learning with microfluidics could significantly expand its adoption and…
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COVID‐19: Machine learning for safe transportation
Entire world has been affected by Covid‐19 pandemic. In fighting against the Covid‐19, social distancing and face mask have a paramount role in freezing the spread of the disease. People are asked to limit their interactions with each other, to reduce the spread of the disease. Here an alert system…
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