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AI for Medical Diagnosis · LearnSpace
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AI for Medical Diagnosis

Курс от DeepLearning.AI
Средний≈ 20.3 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required! This program will give you practical experience in applying cutting-edge machine learning techniques to concrete problems in modern medicine: - In Course 1, you will create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders. - In Course 2, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis. - In Course 3, you will build a treatment effect predictor, apply model interpretation techniques and use natural language processing to extract information from radiology reports. These courses go beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. As a learner, you will be set up for success in this program if you are already comfortable with some of the math and coding behind AI algorithms. You don't need to be an AI expert, but a working knowledge of deep neural networks, particularly convolutional networks, and proficiency in Python programming at an intermediate level will be essential. If you are relatively new to machine learning or neural networks, we recommend that you first take the Deep Learning Specialization, offered by deeplearning.ai and taught by Andrew Ng. The demand for AI practitioners with the skills and knowledge to tackle the biggest issues in modern medicine is growing exponentially. Join us in this specialization and begin your journey toward building the future of healthcare.

Навыки, которые вы освоите

Medical ImagingModel EvaluationData PreprocessingArtificial Neural NetworksDeep LearningImage AnalysisNatural Language ProcessingConvolutional Neural NetworksArtificial IntelligenceApplied Machine LearningModel TrainingStatistical Machine LearningMachine LearningRadiologyComputer VisionRisk ModelingPredictive ModelingDiagnostic RadiologyMachine Learning MethodsPredictive Analytics

Программа курса

3 модулей · 64 учебных материалов

01Disease Detection with Computer Vision30 материалов

Welcome to the AI for Medicine Specialization

Welcome to the Specialization with Andrew and PranavВидеоDemoВидеоRecommended Pre-requisitesВидеоIntake SurveyВнешний инструмент

Учитесь у экспертов

Pranav Rajpurkar

Instructor

Bora Uyumazturk

Curriculum Developer

Amirhossein Kiani

Curriculum Engineer

Eddy Shyu

Instructor

AI for Medical Diagnosis
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 20.3 ч

3 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Украинский, Европейский португальский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Малайский, Венгерский, Польский

Часть программы вашего университета
Join the DeepLearning.AI Forum to ask questions, get support, or share amazing ideas!Чтение

Applications of Computer Vision to Medical Diagnosis

Medical Image DiagnosisВидеоEye Disease and Cancer DiagnosisВидеоData Exploration & Image Pre-ProcessingЛабораторная

Handling Class Imbalance and Small Training Sets

Building and Training a Model for Medical DiagnosisВидеоTraining, Prediction, and LossВидеоImage Classification and Class ImbalanceВидеоBinary Cross Entropy Loss FunctionВидеоImpact of Class Imbalance on Loss CalculationВидеоCounting Labels and Weighted Loss FunctionЛабораторнаяResampling to Achieve Balanced ClassesВидеоMulti-TaskВидеоMulti-task Loss, Dataset size, and CNN ArchitecturesВидеоDensenetЛабораторнаяWorking with a Small Training SetВидеоGenerating More SamplesВидео

Checking your Model Performance

Model TestingВидеоSplitting Data by PatientВидеоPatient Overlap & Data LeakageЛабораторнаяSamplingВидеоGround Truth and Consensus VotingВидеоAdditional Medical TestingВидео

Quiz

Disease Detection with Computer VisionЗадание

Programming Assignment: Chest X-Ray Medical Diagnosis with Deep Learning

(Optional) Downloading your Notebook, Downloading your Workspace and Refreshing your WorkspaceЧтениеAbout the AutoGraderЧтениеChest X-Ray Medical Diagnosis with Deep LearningПрограммирование
02Evaluating Models14 материалов

Key Evaluation Metrics

Sensitivity, Specificity and Evaluation MetricsВидеоAccuracy in Terms of Conditional ProbabilityВидеоSensitivity, Specificity and PrevalenceВидеоPPV, NPVВидеоConfusion MatrixВидеоCalculating PPV in Terms of Sensitivity, Specificity and PrevalenceЧтение

Threshold and Evaluation Metrics

ROC Curve and ThresholdВидеоVarying the ThresholdВидеоROC Curve and ThresholdЛабораторная

Interpreting Confidence Intervals Correctly

Sampling from the Total PopulationВидеоConfidence IntervalsВидео95% Confidence IntervalВидео

Quiz

Evaluating Machine Learning ModelsЗадание

Programming Assignment: Evaluation of Diagnostic Models

Evaluation of Diagnostic ModelsПрограммирование
03Image Segmentation on MRI Images20 материалов

Exploring MRI Data

Medical Image SegmentationВидеоExplore MRI Data & LabelsЛабораторная

Image Segmentation

MRI Data and Image RegistrationВидеоSegmentationВидеоExtract a Sub SectionЛабораторнаяConvolutional Neural networksЧтение2D U-Net and 3D U-NetВидеоMore about U-Net (Optional)ЧтениеU-Net ModelЛабораторнаяData Augmentation for SegmentationВидеоLoss Function for Image SegmentationВидео

Practical Considerations

Different Populations and Diagnostic TechnologyВидеоExternal ValidationВидеоMeasuring Patient OutcomesВидео

Quiz

Segmentation on Medical magesЗадание

End of access to Lab Notebooks

[IMPORTANT] Reminder about end of access to Lab NotebooksЧтение

Programming Assignment: Brain Tumor Auto-Segmentation for Magnetic Resonance Imaging (MRI)

Brain Tumor Auto-Segmentation for Magnetic Resonance Imaging (MRI)Программирование

Summary of AI for Medical Diagnosis

Congratulations!ВидеоAcknowledgementsЧтениеCitationsЧтение