Artificial Intelligence in Medical Sciences and Psychology

Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques.

The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification.

This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, medical students, and researchers.

What You Will Learn

• Apply artificial neural networks when modelling medical data
• Know the standard method for Markov decision making and medical data simulation
• Understand survival analysis methods for investigating data from a clinical trial
• Understand medical record categorization

• Measure personality differences using psychological models Who This Book Is For

  Machine learning engineers and software engineers working on healthcare-related projects involving AI, including healthcare professionals interested in knowing how AI can improve their work setting

  Covers descriptive analysis, visualizing medical data, and developing/evaluating algorithms Explains integrating deep belief networks and CNNs, computer vision, and NLP to find patterns in medical data Presents CNNs to model chest CT scan images and differentiate patients with/without COVID-19

  Autorentext

  Tshepo Chris Nokeri harnesses advanced analytics and artificial intelligence to foster innovation and optimize business performance. In his functional work, he has delivered complex solutions to companies in the mining, petroleum, medical sciences, and manufacturing industries. He initially completed a bachelor's degree in information management. Afterward, he graduated with an Honours degree in business science at the University of the Witwatersrand on a TATA Prestigious Scholarship and a Wits Postgraduate Merit Award. They unanimously awarded him the Oxford University Press Prize.

  Zusammenfassung
  Beginning-Intermediate user level

  Inhalt
  Chapter 1: An Introduction to Artificial Intelligence for Medical Sciences and Psychology.- Chapter 2: Realizing Patterns in Diseases with Neural Networks.- Chapter 3: A Case for COVID-19: Considering the Hidden States and Simulation Results.- Chapter 4: Cancer Segmentation with Neural Networks.- Chapter 5: Modelling Magnetic Resonance Imaging and X-Rays by Executing Artificial Neural Networks.- Chapter 6: A Case for COVID-19 CT Scan Segmentation.- Chapter 7 Modelling Clinical Trial Data.- Chapter 8: Medical Record Categorization.- Chapter 9: A Case for Psychology: Factoring and Clustering Personality Dimensions.