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16 papers · ranked by Valyu relevance

01
PPubMed11 Feb 2007
Applications of Machine Learning in Cancer Prediction and Prognosis
Joseph A. Cruz, David S. Wishart
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to…
79relevance
02
PPubMed10 Jan 2022
Predicting students’ performance in e-learning using learning process and behaviour data
Feiyue Qiu, Guodao Zhang, Xin Sheng, Lei Jiang + 4 more
E-learning is achieved by the deep integration of modern education and information technology, and plays an important role in promoting educational equity. With the continuous expansion of user groups and application areas, it has become increasingly important to effectively ensure the quality of e-learning. Currently…
78relevance
03
PPubMed19 Feb 2022
A Predictive Analysis of Heart Rates Using Machine Learning Techniques
Matthew Oyeleye, Tianhua Chen, Sofya Titarenko, Grigoris Antoniou + 2 more
'Keun Ho Ryu' 'Nipon Theera-Umpon'] Heart disease, caused by low heart rate, is one of the most significant causes of mortality in the world today. Therefore, it is critical to monitor heart health by identifying the deviation in the heart rate very early, which makes it easier to detect and manage the heart’s function…
77relevance
04
PPubMed18 Aug 2025
AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations
Bo Cao, Russell Greiner, Andrew Greenshaw, Jie Sui + 1 more
'Amaryllis Mavragani'] Title: Abstract Recent applications of artificial intelligence (AI) and machine learning in medicine, psychology, and social sciences have led to common terminological confusions. In this paper, we review emerging evidence from systematic reviews documenting widespread misuse of key terms…
77relevance
05
PPubMed2 Jan 2025
Predicting learning achievement using ensemble learning with result explanation Ensemble learning for predicting achievement with explanation
Tingting Tong, Zhen Li, Shahid Akbar
Predicting learning achievement is a crucial strategy to address high dropout rates. However, existing prediction models often exhibit biases, limiting their accuracy. Moreover, the lack of interpretability in current machine learning methods restricts their practical application in education. To overcome these…
77relevance
06
PPubMed28 Apr 2026
Ensemble machine learning framework with SHAP and LIME for accurate early prediction of student success in online learning environments
Essa E. Almazroei
The development of digital learning environments has generated rich educational data capable of supporting early prediction of student outcomes. In this study, seven diverse datasets, spanning demographics, parental education, assessment history, and VLE engagement, were integrated into a unified machine-learning…
75relevance
07
PPubMed24 Mar 2020
Artificial Intelligence in the Intensive Care Unit
Guillermo Gutierrez
This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at [https://www.biomedcentral.com/collections/annualupdate2020](). Further information about the Annual Update in Intensive Care and Emergency Medicine is…
75relevance
08
PPubMed25 Apr 2022
Predictive models for clinical decision making: Deep dives in practical machine learning S. Eloranta and M. Boman Machine learning in practice
Sandra Eloranta, Magnus Boman
The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much attention in the clinical community, thus meriting further investigations into its broader use. In an introduction to predictive modelling using machine learning, we conducted…
74relevance
09
PPubMed18 Oct 2012
Whatever after Next? Adaptive Predictions Based on Short- and Long-Term Memory in Visual Search
Markus Conci, Martina Zellin, Hermann J. Müller
Generating predictions for task-relevant goals is a fundamental requirement of human information processing, as it ensures adaptive success in our complex natural environment. Clark ([4]) proposed a model of hierarchical predictive processing, in which perception, attention, and learning are unified within a coherent…
74relevance
10
PPubMed12 Apr 2024
The origins of unpredictability in life outcome prediction tasks
Ian Lundberg, Rachel Brown-Weinstock, Susan Clampet-Lundquist, Sarah Pachman + 4 more
'Sarah Pachman' 'Timothy J. Nelson' 'Vicki Yang' 'Kathryn Edin' 'Matthew J. Salganik'] Title: Significance Scientists and decision-makers routinely make life outcome predictions: they use information from the past to predict what will happen to someone in the future. These predictions, whether made by human experts or…
73relevance
11
PPubMed17 Jun 2022
Prospects and Challenges of Using Machine Learning for Academic Forecasting
Edeh Michael Onyema, Khalid K. Almuzaini, Fergus Uchenna Onu, Devvret Verma + 3 more
'Devvret Verma' 'Ugboaja Samuel Gregory' 'Monika Puttaramaiah' 'Rockson Kwasi Afriyie'] The study examines the prospects and challenges of machine learning (ML) applications in academic forecasting. Predicting academic activities through machine learning algorithms presents an enhanced means to accurately forecast…
72relevance
12
PPubMed10 Jan 2020
Machine Learning in Psychometrics and Psychological Research
Graziella Orrù, Merylin Monaro, Ciro Conversano, Angelo Gemignani + 1 more
'Giuseppe Sartori'] Recent controversies about the level of replicability of behavioral research analyzed using statistical inference have cast interest in developing more efficient techniques for analyzing the results of psychological experiments. Here we claim that complementing the analytical workflow of…
71relevance
13
PPubMed13 Sep 2022
Predicting Outcome in Patients with Brain Injury: Differences between Machine Learning versus Conventional Statistics
Antonio Cerasa, Gennaro Tartarisco, Roberta Bruschetta, Irene Ciancarelli + 7 more
'Irene Ciancarelli' 'Giovanni Morone' 'Rocco Salvatore Calabrò' 'Giovanni Pioggia' 'Paolo Tonin' 'Marco Iosa' 'Amedeo Amedei' 'Jessica Mandrioli'] Defining reliable tools for early prediction of outcome is the main target for physicians to guide care decisions in patients with brain injury. The application of machine…
71relevance
14
PPubMed11 Dec 2021
Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis
Stijn Denissen, Oliver Y. Chén, Johan De Mey, Maarten De Vos + 4 more
'Jeroen Van Schependom' 'Diana Maria Sima' 'Guy Nagels' 'Cristina M. Ramo-Tello'] Multiple sclerosis (MS) manifests heterogeneously among persons suffering from it, making its disease course highly challenging to predict. At present, prognosis mostly relies on biomarkers that are unable to predict disease course on an…
70relevance
15
PPubMed3 Jun 2022
Empirical analyses and simulations showed that different machine and statistical learning methods had differing performance for predicting blood pressure
Peter C. Austin, Frank E. Harrell Jr, Douglas S. Lee, Ewout W. Steyerberg
Machine learning is increasingly being used to predict clinical outcomes. Most comparisons of different methods have been based on empirical analyses in specific datasets. We used Monte Carlo simulations to determine when machine learning methods perform better than statistical learning methods in a specific setting.…
68relevance
16
PPubMed29 Nov 2024
A hybrid model integrating recurrent neural networks and the semi-supervised support vector machine for identification of early student dropout risk
Huong Nguyen Thi Cam, Aliza Sarlan, Noreen Izza Arshad, Bilal Alatas
Background Student dropout rates are one of the major concerns of educational institutions because they affect the success and efficacy of them. In order to help students continue their learning and achieve a better future, there is a need to identify the risk of student dropout. However, it is challenging to…
65relevance

Results for predictive learning

Applications of Machine Learning in Cancer Prediction and Prognosis

Predicting students’ performance in e-learning using learning process and behaviour data

A Predictive Analysis of Heart Rates Using Machine Learning Techniques

AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations

Predicting learning achievement using ensemble learning with result explanation Ensemble learning for predicting achievement with explanation

Ensemble machine learning framework with SHAP and LIME for accurate early prediction of student success in online learning environments

Artificial Intelligence in the Intensive Care Unit

Predictive models for clinical decision making: Deep dives in practical machine learning S. Eloranta and M. Boman Machine learning in practice

Whatever after Next? Adaptive Predictions Based on Short- and Long-Term Memory in Visual Search

The origins of unpredictability in life outcome prediction tasks

Prospects and Challenges of Using Machine Learning for Academic Forecasting

Machine Learning in Psychometrics and Psychological Research

Predicting Outcome in Patients with Brain Injury: Differences between Machine Learning versus Conventional Statistics

Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis

Empirical analyses and simulations showed that different machine and statistical learning methods had differing performance for predicting blood pressure

A hybrid model integrating recurrent neural networks and the semi-supervised support vector machine for identification of early student dropout risk

Applications of Machine Learning in Cancer Prediction and Prognosis

Predicting students’ performance in e-learning using learning process and behaviour data

A Predictive Analysis of Heart Rates Using Machine Learning Techniques

AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations

Predicting learning achievement using ensemble learning with result explanation Ensemble learning for predicting achievement with explanation

Ensemble machine learning framework with SHAP and LIME for accurate early prediction of student success in online learning environments

Artificial Intelligence in the Intensive Care Unit

Predictive models for clinical decision making: Deep dives in practical machine learning S. Eloranta and M. Boman Machine learning in practice

Whatever after Next? Adaptive Predictions Based on Short- and Long-Term Memory in Visual Search

The origins of unpredictability in life outcome prediction tasks

Prospects and Challenges of Using Machine Learning for Academic Forecasting

Machine Learning in Psychometrics and Psychological Research

Predicting Outcome in Patients with Brain Injury: Differences between Machine Learning versus Conventional Statistics

Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis

Empirical analyses and simulations showed that different machine and statistical learning methods had differing performance for predicting blood pressure

A hybrid model integrating recurrent neural networks and the semi-supervised support vector machine for identification of early student dropout risk