Applying machine learning for automated classification of biomedical data in subject-independent settings. ([2019])
- Record Type:
- Book
- Title:
- Applying machine learning for automated classification of biomedical data in subject-independent settings. ([2019])
- Main Title:
- Applying machine learning for automated classification of biomedical data in subject-independent settings
- Further Information:
- Note: Thuy T. Pham.
- Authors:
- Pham, Thuy T
- Contents:
- Introduction .-Background .-Algorithms .-Point Anomaly Detection: Application to Freezing of Gait Monitoring .-Collective Anomaly Detection: Application to Respiratory Artefact Removals.-Spike Sorting: Application to Motor Unit Action Potential Discrimination .-Conclusion.
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2019
- Extent:
- 1 online resource (xv, 107 pages), illustrations (some color)
- Subjects:
- 006.3/1
Engineering
Machine learning
Artificial intelligence -- Medical applications
Medical informatics
COMPUTERS / General
Computers -- Database Management -- Data Mining
Computers -- Intelligence (AI) & Semantics
Science -- Life Sciences -- Anatomy & Physiology
Data mining
Artificial intelligence
Molecular biology
Biomedical engineering
Data mining
Bioinformatics
Technology & Engineering -- Engineering (General)
Biomedical engineering
Electronic books - Languages:
- English
- ISBNs:
- 9783319986753
3319986759 - Related ISBNs:
- 9783319986746
- Notes:
- Note: Includes bibliographical references.
Note: Online resource; title from PDF title page (SpringerLink, viewed August 28, 2018). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.323617
- Ingest File:
- 01_261.xml