Machine Learning and AI for Healthcare -Bookswagon
Home > Computer & Internet > Computer science > Artificial intelligence > Machine learning > Machine Learning and AI for Healthcare
Machine Learning and AI for Healthcare

Machine Learning and AI for Healthcare


     0     
5
4
3
2
1



International Edition


About the Book

Chapter 1: Introduction: Learning for Healthcare Chapter Goal: Introduction to book and topics to be covered No of pages 10Sub -Topics1. What is AI, data science, machine and deep learning2. The case for learning from data3. Evolution of big data/learning/Analytics 3.04. Practical examples of how data can be used to learn within healthcare settings5. Conclusion
Chapter 2: Big Data Chapter Goal: To understand data required for learning and how to ensure valid data for outcome veracityNo of pages: 35Sub - Topics 1. What is data, sources of data and what types of data is there? little vs big data and the advantages/disadvantages with such data sets. Structured vs. unstructured data.2. Massive data - management and complexities3. The key aspects required of data, in particular, validity to ensure that only useful and relevant information4. How to use big data for learning (use cases)5. Turning data into information - how to collect data that can be used to improve health outcomes and examples of how to collect such data6. Challenges faced as part of the use of big data7. Data governance
Chapter 3: What is Machine learning?Chapter Goal: To introduce machine learning, identify/demystify types of learning and provide information of popular algorithms and their applicationsNo of pages: 45Sub - Topics: 1. Introduction - what is learning?2. Differences/similarities between: what is AI, data science, machine learning, deep learning3. History/evolution of learning4. Learning algorithms - popular types/categories, complex examples of machine learning models, applications and their mathematical basis5. Software(s) used for learning6. Code samples
Chapter 4: Machine Learning in HealthcareChapter Goal: A comprehensive understanding of key concepts related to learning systems and the practical application of machine learning within healthcare settings No of pages: 50Sub - Topics: 1. Understanding Tasks, Performance and Experience to optimize algorithms and outcomes 2. Identification of algorithms to be used in healthcare applications for: predictive analysis, perspective analysis, inference, modeling, probability estimation, NLP etc and common uses3. Real-time analysis and analytics4. Machine learning best practices5. Neural networks, ANNs, deep learning6. Code samples
Chapter 5: Evaluating Learning for IntelligenceChapter Goal: To understand how to evaluate learning algorithms, how to choose the best evaluation technique/approach for analysisNo of pages: 301. How to evaluate machine learning systems 2. Methodologies for evaluating outputs3. Improving your intelligence4. Advanced analytics5. Real-world examples of evaluations
Chapter 6: Ethics of intelligenceChapter Goal: To understand the hurdles that must be addressed in AI/machine learning and also overcome on both a micro- and macro-level to enable enhanced health intelligence No of pages: 251. The benefits of big data and machine learning2. The disadvantages of big data and machine learning - who owns the data, distributing the data, should patients/people be told what the results are (e.g. data demonstrates risk of cancer)3. Data for good, or data for bad?4. Topics that require addressing in order to ensure ease, efficiency and safety of outputs5. Do we need t
About the Author:

Arjun Panesar is the founder of Diabetes Digital Media (DDM), the world's largest diabetes community and provider of evidence-based digital health interventions. He holds an honors degree (MEng) in computing and artificial intelligence from Imperial College, London. He has a decade of experience in big data and affecting user outcomes, and leads the development of intelligent, evidence-based digital health interventions that harness the power of big data and machine learning to provide precision patient care to patients, health agencies, and governments worldwide.

Arjun's work has received international recognition and was featured by the BBC, Forbes, New Scientist, and The Times. He has received innovation, business, and technology awards, including being named the top app for prevention of type 2 diabetes.

Arjun is an advisor to the Information School, at the University of Sheffield, Fellow to the NHS Innovation Accelerator, and was recognized by Imperial College as an Emerging Leader in 2020 for his contribution and impact to society.



Best Sellers



Product Details
  • ISBN-13: 9781484265369
  • Publisher: Apress
  • Publisher Imprint: Apress
  • Height: 254 mm
  • No of Pages: 407
  • Spine Width: 23 mm
  • Weight: 807 gr
  • ISBN-10: 148426536X
  • Publisher Date: 09 Jan 2021
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Sub Title: Big Data for Improved Health Outcomes
  • Width: 178 mm


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Machine Learning and AI for Healthcare
Apress -
Machine Learning and AI for Healthcare
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Machine Learning and AI for Healthcare

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    New Arrivals



    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!