Machine learning approach for improving decision support in ICU
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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| フォーマット: | 学位論文 |
| 言語: | English |
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BRAC University
2019
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| オンライン･アクセス: | http://hdl.handle.net/10361/11602 |
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10361-116022022-01-26T10:15:51Z Machine learning approach for improving decision support in ICU Siddiquee, Mohib Billah Fuad, Mostofa Jamil Azmain, Md. Fahim Alam, Md. Ashraful Department of Computer Science and Engineering, BRAC University ICU Machine learning Artificial intelligence 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 37-41). Patients in the intensive care unit (ICU) receive a deep observation for controlling and responding to their rapidly changing physiological conditions. The quality of their care depends on clinical staff combining large amounts of clinical data to understand the severity of their illness. Actually in real time doctors and nurses have to take care of huge amount of data. Sometimes, they cannot focus on all the parameters at the same time. After collecting all the parameters, they take decisions. A lack of early recognition of physiologic decline can play a major role in failure to rescue patients. Early prediction is one of the important tasks in the ICU. In this paper, we propose a machine learning approach to improve decision support in ICU. In the proposed model decision tree will be used to predict the future health condition of patients. The curve of the decision tree of the proposed model will show how severe the patient‘s condition is. It will also show the health improvements and decrements. In this model there is option for controlling the lifesaving machines of ICU like ventilation machine, blood warmer machine and syringe pump machine. To control the machines this model uses logistic regression algorithm. It will use some independent variables to predict the decision of automatic intervention. Using the proposed model doctors can easily monitor the health of ICU patients. As it predicts risks, doctors can take early preparation for worst situation. Automatic intervention decisions for ICU machines can save lives in critical moments. As a whole, the model is specially designed for coronary care unit of ICU. Mohib Billah Siddiquee Mostofa Jamil Fuad Md. Fahim Azmain B. Computer Science and Engineering 2019-03-20T05:35:52Z 2019-03-20T05:35:52Z 2018 2018-07 Thesis ID 12201043 ID 13301081 ID 14201057 http://hdl.handle.net/10361/11602 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. 41 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
ICU Machine learning Artificial intelligence |
| spellingShingle |
ICU Machine learning Artificial intelligence Siddiquee, Mohib Billah Fuad, Mostofa Jamil Azmain, Md. Fahim Machine learning approach for improving decision support in ICU |
| 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 |
Alam, Md. Ashraful |
| author_facet |
Alam, Md. Ashraful Siddiquee, Mohib Billah Fuad, Mostofa Jamil Azmain, Md. Fahim |
| format |
Thesis |
| author |
Siddiquee, Mohib Billah Fuad, Mostofa Jamil Azmain, Md. Fahim |
| author_sort |
Siddiquee, Mohib Billah |
| title |
Machine learning approach for improving decision support in ICU |
| title_short |
Machine learning approach for improving decision support in ICU |
| title_full |
Machine learning approach for improving decision support in ICU |
| title_fullStr |
Machine learning approach for improving decision support in ICU |
| title_full_unstemmed |
Machine learning approach for improving decision support in ICU |
| title_sort |
machine learning approach for improving decision support in icu |
| publisher |
BRAC University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/11602 |
| work_keys_str_mv |
AT siddiqueemohibbillah machinelearningapproachforimprovingdecisionsupportinicu AT fuadmostofajamil machinelearningapproachforimprovingdecisionsupportinicu AT azmainmdfahim machinelearningapproachforimprovingdecisionsupportinicu |
| _version_ |
1814308371138871296 |