Academic Articles & Research Papers

Understanding Machine Learning

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book prov...

Machine learning for precision medicine

Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...

Machine Learning

Towards instance-wise calibration: local amortized diagnostics and reshaping of conditional densities (LADaR)

Key science questions, such as galaxy distance estimation and weather forecasting, often require knowing the full predictive distribution of a target variable Y given complex inputs X . Despite recent advances in machine learning and physic...

Bioinformatics the machine learning approach

In this book Pierre Baldi and Soren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed both at biologists and biochemists who nee...

Machine learning: Trends, perspectives, and prospects

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and a...

Machine Learning for Sociology

Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...

Overfitting and undercomputing in machine learning

suggests a reasonable line of research: find algorithms that can search the hypothesis class better. Hence, there is been extensive research in applying second-order methods to fit neural networks and in conducting much more thorough search...

Introduction to Machine Learning

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict ...

Artificial intelligence: Implications for the future of work

Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a smal...

Leveraging Artificial Intelligence to Predict Posterior Malleolus Fracture Extension in Tibial Shaft Fractures

Research Type: Level 3 - Retrospective cohort study, Case-control study, Meta-analysis of Level 3 studies Introduction/Purpose: Occult posterior malleolar fractures (PMFs) are reported commonly in tibial shaft fractures. Presurgical identif...

Research on Oil and Gas Pipeline Leakage Detection Based on MSCNN-Transformer

The leakage detection of oil and gas is very important for the safe operation of pipelines. The existing working condition recognition methods have limitations in processing and capturing complex multi-category leakage signal characteristic...

An integrated method for color correction based on color constancy for early mural images in Mogao Grottoes

Restoring the correct or realistic color of a cultural heritage object is a crucial problem for imaging techniques. Digital images often have undesired color casts due to adverse effects caused by unstable illuminant conditions, vignetting,...

Evolution of strategies in iterated games: a deep multi-agent reinforcement learning approach with hybrid genetic and CMA-ES optimization

The emergence of cooperation among self-interested agents in social dilemmas remains a central unsolved problem in evolutionary game theory, multi-agent systems, and behavioral science. While memory-one reciprocal strategies such as Tit-for...

A Generalized Framework for Adopting Regression-Based Predictive Modeling in Manufacturing Environments

In this paper, the growing significance of data analysis in manufacturing environments is exemplified through a review of relevant literature and a generic framework to aid the ease of adoption of regression-based supervised learning in man...

Perturbation Theory for Quasinilpotents in Banach Algebras

In this paper, we prove the following result by perturbation technique. If q is a quasinilpotent element of a Banach algebra and spectrum of p + q for any other quasinilpotent p contains at most n values then q n = 0 . Appl...

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

A review of prediction methods for moving target trajectories

With the rapid emergence of mobile terminal equipment in intelligent transportation system, the deep understanding and accurate prediction of moving target trajectories are capable of reducing the traffic accident probability, and promoting...

Health Equity Journal: Special Issue Guest Editorial

The practices of contemporary clinical decision-making and care rely heavily on racial biological essentialism, which is a set of ideas originating in modern science that describes populations as comprising distinct subpopulations with uniq...

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry

Abstract To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monito...