Results 111 to 120 of about 8,838,426 (323)

Comparing XGBoost and Double Machine Learning for Predicting the Nitrogen Requirement of Rice

Remote Sensing
Estimating how crop yield responds to site-specific nitrogen (N) fertilization is essential for maximizing yield potential under variable field conditions.
Miltiadis Iatrou, Spiros Mourelatos, Christos Karydas   +2 more
doaj   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

A novel extended Granger Causal model approach demonstrates brain hemispheric differences during face recognition learning [PDF]

, 2009
Two main approaches in exploring causal relationships in biological systems using time-series data are the application of Dynamic Causal model (DCM) and Granger Causal model (GCM).
Kendrick Keith M., Feng, Jianfeng, Jianfeng Feng, Kendrick, Keith M., Ge Tian, Ge, Tian, Keith M Kendrick, Tian Ge, Feng Jianfeng   +8 more
core   +2 more sources

Targeted Active Learning for Bayesian Decision-Making

Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way.
Kaski, Samuel, Tiulpin, Aleksei, Filstroff, Louis, Sundin, Iiris, Kylmäoja, Juuso, Mikkola, Petrus   +5 more
core   +1 more source

Diabetes Prediction Through Linkage of Causal Discovery and Inference Model with Machine Learning Models

Biomedicines
Background/Objectives: Diabetes is a dangerous disease that is accompanied by various complications, including cardiovascular disease. As the global diabetes population continues to increase, it is crucial to identify its causes.
Mi Jin Noh, Yang Sok Kim
doaj   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

Utilizing deep learning-based causal inference to explore vancomycin’s impact on continuous kidney replacement therapy necessity in blood culture-positive intensive care unit patients

Microbiology Spectrum
Patients with positive blood cultures in the intensive care unit (ICU) are at high risk for septic acute kidney injury requiring continuous kidney replacement therapy (CKRT), especially when treated with vancomycin.
Min Woo Kang, Yoonjin Kang
doaj   +1 more source

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, EarlyView.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +1 more source

A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems

The evaluation of fairness models in Machine Learning involves complex challenges, such as defining appropriate metrics, balancing trade-offs between utility and fairness, and there are still gaps in this stage. This work presents a novel multi-objective
Özbulak, Gökhan, Jimenez-del-Toro, Oscar, Anjos, André, Berton, Lilian, Fatoretto, Maíra   +4 more
core   +1 more source

Robust double machine learning model with application to omics data

BMC Bioinformatics
Background Recently, there has been a growing interest in combining causal inference with machine learning algorithms. Double machine learning model (DML), as an implementation of this combination, has received widespread attention for their expertise in
Xuqing Wang, Yahang Liu, Guoyou Qin, Yongfu Yu   +3 more
doaj   +1 more source