A machine learning approach on classifying orthopedic patients based on their biomechanical features
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
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| Idioma: | English |
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BRAC University
2018
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| Acesso em linha: | http://hdl.handle.net/10361/10119 |
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10361-101192022-01-26T10:23:14Z A machine learning approach on classifying orthopedic patients based on their biomechanical features Hasan, Kamrul Islam, Safkat Samio, Md. Mehfil Rashid Khan Chakrabarty, Amitabha Department of Computer Science and Engineering, BRAC University Orthopedic Health condition Machine learning Decision tree Algorithm This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 46-48). A person’s orthopedic health condition can be detected from his biomechanical features. Application of machine learning algorithms in medical science is not new. Different algorithms are applied to detect diseases and classify patients accordingly. This paper aims to assist specialists to predict the type of orthopedic disease. In this paper we have applied various machine learning algorithms to find out which one works most accurately to detect and classify orthopedic patients. Each of the patients in the dataset is represented by six biomechanical attributes derived from the shape and orientation of pelvis and lumbar spine. We performed our operation in two stages and got an average accuracy of more than 90 percent for most of the algorithms, whereas Decision Tree (DT) algorithm stood out from the rest providing 99% accuracy. Kamrul Hasan Safkat Islam Md. Mehfil Rashid Khan Samio B. Computer Science and Engineering 2018-05-10T08:50:19Z 2018-05-10T08:50:19Z 2018 2018-04 Thesis ID 13101102 ID 13301099 ID 13101029 http://hdl.handle.net/10361/10119 en BRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 48 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Orthopedic Health condition Machine learning Decision tree Algorithm |
| spellingShingle |
Orthopedic Health condition Machine learning Decision tree Algorithm Hasan, Kamrul Islam, Safkat Samio, Md. Mehfil Rashid Khan A machine learning approach on classifying orthopedic patients based on their biomechanical features |
| description |
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. |
| author2 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Hasan, Kamrul Islam, Safkat Samio, Md. Mehfil Rashid Khan |
| format |
Thesis |
| author |
Hasan, Kamrul Islam, Safkat Samio, Md. Mehfil Rashid Khan |
| author_sort |
Hasan, Kamrul |
| title |
A machine learning approach on classifying orthopedic patients based on their biomechanical features |
| title_short |
A machine learning approach on classifying orthopedic patients based on their biomechanical features |
| title_full |
A machine learning approach on classifying orthopedic patients based on their biomechanical features |
| title_fullStr |
A machine learning approach on classifying orthopedic patients based on their biomechanical features |
| title_full_unstemmed |
A machine learning approach on classifying orthopedic patients based on their biomechanical features |
| title_sort |
machine learning approach on classifying orthopedic patients based on their biomechanical features |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/10119 |
| work_keys_str_mv |
AT hasankamrul amachinelearningapproachonclassifyingorthopedicpatientsbasedontheirbiomechanicalfeatures AT islamsafkat amachinelearningapproachonclassifyingorthopedicpatientsbasedontheirbiomechanicalfeatures AT samiomdmehfilrashidkhan amachinelearningapproachonclassifyingorthopedicpatientsbasedontheirbiomechanicalfeatures AT hasankamrul machinelearningapproachonclassifyingorthopedicpatientsbasedontheirbiomechanicalfeatures AT islamsafkat machinelearningapproachonclassifyingorthopedicpatientsbasedontheirbiomechanicalfeatures AT samiomdmehfilrashidkhan machinelearningapproachonclassifyingorthopedicpatientsbasedontheirbiomechanicalfeatures |
| _version_ |
1814309623346233344 |