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Machine Learning for Healthcare Applications · LearnSpace
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Machine Learning for Healthcare Applications

Курс от SkillUp
Средний≈ 9.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Build the machine learning foundation for healthcare demands! Learn how to turn complex clinical data into models that drive decision support, early warning, diagnostic assistance, and personalized treatment insights. This course equips you with practical machine learning skills for real-world healthcare analytics. You will apply supervised, unsupervised, and temporal modeling techniques that match common healthcare data realities and clinical use cases. You’ll learn to frame clinical prediction problems, construct features from structured and time-based data, and develop classification and regression models for healthcare settings. You’ll also discover patient subgroups using clustering and dimensionality reduction and interpret patterns in patient populations. Across the course, you’ll focus on interpretability, robustness, and healthcare-appropriate evaluation metrics tied to clinical risk and patient safety. In hands-on labs, you’ll build a Readmission Risk Classifier, cluster patients for phenotype discovery, visualize populations with dimensionality reduction, engineer temporal features for an early warning model, and compare models using ROC, PR, calibration, and threshold-based utility analysis.

Навыки, которые вы освоите

Supervised LearningModel EvaluationUnsupervised LearningTime Series Analysis and ForecastingForecastingLogistic RegressionApplied Machine LearningDimensionality ReductionPredictive ModelingFeature EngineeringHealth InformaticsMachine LearningMachine Learning AlgorithmsDecision Tree LearningPredictive AnalyticsModel TrainingClassification AlgorithmsData PreprocessingClinical InformaticsMachine Learning Methods

Программа курса

4 модулей · 66 учебных материалов

01Supervised Learning for Clinical Prediction22 материалов

Welcome to the Course

Course IntroductionВидеоCourse OverviewЧтениеReading: How to Make the Most of This CoursePLUGINSpecialization OverviewВидео

Framing Clinical Problems as Supervised Learning Tasks

Учитесь у экспертов

Ramesh Sannareddy

Data Engineering Subject Matter Expert

SkillUp

Преподаватель курса

Machine Learning for Healthcare Applications
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Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 9.7 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский

Часть программы вашего университета
Turning Clinical Questions into Predictive Modeling TasksВидео
Target Leakage and Data Pitfalls in Healthcare ModelingВидео
Spotting Predictions in Everyday QuestionsОбсуждение
Practice Quiz: Framing Clinical Problems as Supervised Learning TasksЗадание
Framing Clinical Problems as Supervised Learning TasksDIALOGUE

Classification Models for Diagnosis and Risk Prediction

Logistic Regression for Clinical Risk EstimationВидеоTree-Based Models for Nonlinear Patterns in EHR DataВидеоReading: Advanced Supervised Learning Models and Ensemble TechniquesPLUGINLab: Building a Readmission Risk ClassifierЧтениеPractice Quiz: Classification Models for Diagnosis and Risk PredictionЗаданиеClassification Models for Diagnosis and Risk PredictionDIALOGUE

Regression Models for Clinical Outcomes

Regression Models for Continuous Clinical OutcomesВидеоHandling Imbalanced and Rare Event OutcomesВидеоReading: Common Supervised-Learning Applications and Feature DesignPLUGINActivity: Choosing Baseline Predictive ModelsDIALOGUEPractice Quiz: Regression Models for Clinical OutcomesЗадание

Module Summary and Assessment

Module Summary: Supervised Learning for Clinical PredictionЧтениеGraded Quiz: Supervised Learning for Clinical PredictionЗадание
02Unsupervised Learning and Patient Phenotyping18 материалов

Clustering Methods for Patient Groups

Use of Clustering Algorithms in Clinical ContextsВидеоReading: Design Considerations for Phenotyping StudiesPLUGINLab: Clustering Patients for Phenotype DiscoveryЧтениеActivity: Phenotype DetectivePLUGINPractice Quiz: Clustering Methods for Patient GroupsЗаданиеClustering Methods for Patient PhenotypingDIALOGUE

Dimensionality Reduction and Representation Learning

Dimensionality Reduction for Clinical Data Exploration ВидеоRepresentation Learning for Complex Clinical DataВидеоLab: Visualizing Patient Populations with Dimensionality ReductionЧтениеVisualizing Patient Populations with Dimensionality ReductionОбсуждениеPractice Quiz: Dimensionality Reduction and Representation LearningЗаданиеDimensionality Reduction and Representation LearningDIALOGUE

Evaluating Unsupervised Models

Evaluating Cluster Quality, Stability, and RobustnessВидеоReading: Case Studies in Data-Driven PhenotypingPLUGINActivity: When can Clusters be Trusted?DIALOGUEPractice Quiz: Evaluating Unsupervised ModelsЗадание

Module Summary and Assessment

Module Summary: Unsupervised Learning and Patient PhenotypingЧтениеGraded Quiz: Unsupervised Learning and Patient PhenotypingЗадание
03Time Series Modeling and Model Evaluation18 материалов

Temporal Data and Feature-Based Approaches

Working with Irregular Clinical Time SeriesВидеоReading: Feature Engineering for Temporal ModelingPLUGINLab: Building Temporal Features for an Early Warning ModelЧтениеUsing Temporal Features in Early Warning ModelsОбсуждениеPractice Quiz: Temporal Data and Feature-Based ApproachesЗаданиеTemporal Data and Feature-Based Modeling in HealthcareDIALOGUE

Classical Time-Series Models

Classical Forecasting Approaches in HealthcareВидеоReading: State-Space Models, Kalman Filters, and Survival AnalysisPLUGINActivity: A Week in the Emergency Department (ED)PLUGINPractice Quiz: Classical Time-Series ModelsЗаданиеClassical Time-Series Models in HealthcareDIALOGUE

Evaluation and Clinical Validation

Evaluating Models with ROC and PR CurvesВидеоCalibration, Thresholding, and Clinical UtilityВидеоReading: Model InterpretabilityPLUGINLab: Evaluating and Comparing Clinical Prediction ModelsЧтениеPractice Quiz: Evaluation and Clinical ValidationЗадание

Module Summary and Assessment

Module Summary: Time Series Modeling and Model EvaluationЧтениеGraded Quiz: Time Series Modeling and Model EvaluationЗадание
04Final Project, Exam, and Wrap-Up8 материалов

Final Project

Final Project OverviewЧтениеFinal Project: Designing an Early Warning System for Clinical DeteriorationВзаимная проверкаComparing Your WorkОбсуждение

Summary, Glossary, and Final Exam

Course SummaryВидеоCourse Glossary: Machine Learning for Healthcare ApplicationsPLUGINFinal Exam: Machine Learning for Healthcare ApplicationsЗадание

Course Wrap-Up

Congratulations and Next StepsЧтениеTeam and AcknowledgmentsЧтение