214.423 hasil untuk machine learning
Menampilkan 241–260 · 1,20 detik · RSS
-
Artikel Jurnal Teks lengkap
Machine learning-driven new material discovery
…the current need for new materials. Now, a newly proposed idea of using machine learning to explore new materials is becoming popular. In this paper, we review this research paradigm of applying machine learning in material discovery, including data preprocessing, feature engineering, machine…
-
Artikel Jurnal Teks lengkap
Machine learning for morbid glomerular hypertrophy
A practical research method integrating data-driven machine learning with conventional model-driven statistics is sought after in medicine. Although glomerular hypertrophy (or a large renal corpuscle) on renal biopsy has pathophysiological implications, it is often misdiagnosed as…
-
Artikel Jurnal Teks lengkap
Machine Learning Applications for Chemical Reactions
Machine learning (ML) approaches have enabled rapid and efficient molecular property predictions as well as the design of new novel materials. In addition to great success for molecular problems, ML techniques are applied to various chemical reaction problems that require huge costs to solve with…
-
Artikel Jurnal Teks lengkap
Supervised machine learning: A brief primer
Machine learning is increasingly used in mental health research and has the potential to advance our understanding of how to characterize, predict, and treat mental disorders and associated adverse health outcomes (e.g., suicidal behavior). Machine learning offers new tools to overcome challenges…
-
Artikel Jurnal Teks lengkap
Machine learning applications in drug development
Due to the huge amount of biological and medical data available today, along with well-established machine learning algorithms, the design of largely automated drug development pipelines can now be envisioned. These pipelines may guide, or speed up, drug discovery; provide a better understanding of…
-
Artikel Jurnal Teks lengkap
Machine learning in chemical reaction space
Chemical compound space refers to the vast set of all possible chemical compounds, estimated to contain 10(60) molecules. While intractable as a whole, modern machine learning (ML) is increasingly capable of accurately predicting molecular properties in important subsets. Here, we therefore engage…
-
Artikel Jurnal Teks lengkap
Integrating Machine Learning with Human Knowledge
Machine learning has been heavily researched and widely used in many disciplines. However, achieving high accuracy requires a large amount of data that is sometimes difficult, expensive, or impractical to obtain. Integrating human knowledge into machine learning can significantly reduce data…
-
Artikel Jurnal Teks lengkap
Machine learning–based prediction of transfusion
…patient. We therefore investigated the precision of four different machine learning–based prediction algorithms to predict transfusion, massive transfusion, and the number of transfusions in patients admitted to a hospital. STUDY DESIGN AND METHODS: This was a retrospective, observational study in…
-
Artikel Jurnal Teks lengkap
Machine learning for modeling animal movement
…effects on movement behavior and to fill in missing tracking data. Machine Learning and Deep learning algorithms are powerful and flexible predictive modeling tools but have rarely been applied to animal movement data. In this study we present a general framework for predicting animal movement that…
-
Artikel Jurnal Teks lengkap
Machine learning in oncology: a review
Machine learning is a set of techniques that promise to greatly enhance our data-processing capability. In the field of oncology, ML presents itself with a wealth of possible applications to the research and the clinical context, such as automated diagnosis and precise treatment modulation. In this…
-
Artikel Jurnal Teks lengkap
Machine Learning for Absorption Cross Sections
[Image: see text] We present a machine learning (ML) method to accelerate the nuclear ensemble approach (NEA) for computing absorption cross sections. ML-NEA is used to calculate cross sections on vast ensembles of nuclear geometries to reduce the error due to insufficient statistical sampling. The…
-
Artikel Jurnal Teks lengkap
Machine Learning Guidance for Connection Tableaux
…tableaux proof search, including a consistent Skolemisation procedure for machine learning. Then, we show two guidance methods based on machine learning, namely reordering of proof steps with Naive Bayesian probabilities, and expansion of a proof search tree with Monte Carlo Tree Search.
-
Artikel Jurnal Teks lengkap
Machine Learning in Arrhythmia and Electrophysiology
Machine learning (ML), a branch of artificial intelligence (AI), where machines learn from big data, is at the crest of a technological wave of change sweeping society. Cardiovascular medicine is at the forefront of many ML applications, and there is a significant effort to bring them into…
-
Artikel Jurnal Teks lengkap
Machine Learning Techniques for Mitoses Classification
BACKGROUND. Pathologists analyze biopsy material at both the cellular and structural level to determine diagnosis and cancer stage. Mitotic figures are surrogate biomarkers of cellular proliferation that can provide prognostic information; thus, their precise detection is an important factor for…
-
Artikel Jurnal Teks lengkap
Machine learning-enabled multiplexed microfluidic sensors
…but also prone to the bias of the user and low accuracy. Integrating machine learning (ML) with the image acquisition capability of smartphones as well as increasing computing power could address the need for high-throughput, accurate, and automatized detection, data processing, and quantification…
-
Artikel Jurnal Teks lengkap
Machine Learning Prediction of Antimicrobial Peptides
…peptide prediction program. It also facilitated the testing of the first machine learning algorithms. This chapter provides an overview of machine-learning predictions of AMPs. Most of the predictors, such as AntiBP, CAMP, and iAMPpred, involve a single-label prediction of antimicrobial activity…
-
Artikel Jurnal Teks lengkap
Practical machine learning for disease diagnosis
Deep learning neural networks are a powerful tool in the analytical toolbox of modern microscopy, but they come with an exacting requirement for accurately annotated, ground truth cell images. Otesteanu et al. (2021) elegantly streamline this process, implementing network training by using…
-
Artikel Jurnal Teks lengkap
Applications of Machine Learning in Cardiology
…the healthcare industry, especially in the clinical arena of cardiology. Machine learning (ML) algorithms are making substantial progress in various subspecialties of cardiology. This will have a positive impact on patient care and move the field towards precision medicine. In this review article…
Menampilkan maksimal 50 halaman. Persempit pencarian dengan filter untuk hasil yang lebih spesifik.