| Type of Material: | Thesis |
| Title: | Early sepsis prediction in intensive care patients using machine learning techniques |
| Researcher: | Shenoy, Aparna |
| Guide: | Rao, Babu K |
| Department: | School of Engineering & Technology |
| Publisher: | CMR University, Bangalore |
| Place: | Bangalore |
| Year: | 2022 |
| Language: | English |
| Subject: | Sepsis Prediction | Machine Learning | Computer Science and Applications | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; School of Engineering & Technology, CMR University, Bangalore, Bangalore; 2022; 15RE01001 |
| 000 | 00000ntm a2200000ua 4500 | |
| 001 | 446586 | |
| 003 | IN-AhILN | |
| 005 | 2023-05-12 11:04:55 | |
| 008 | __ | 230512t2022||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_446586 |
| 040 | __ | |aCMRB_560043|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aShenoy, Aparna|eResearcher |
| 110 | __ | |aSchool of Engineering & Technology|bCMR University, Bangalore|dBangalore|ein|0U-0723 |
| 245 | __ | |aEarly sepsis prediction in intensive care patients using machine learning techniques |
| 260 | __ | |bCMR University, Bangalore|c2022|aBangalore |
| 502 | __ | |cSchool of Engineering & Technology, CMR University, Bangalore, Bangalore|d2022|o15RE01001|bPhD |
| 518 | __ | |oDate of Notification|d2022-11-23 |
| 518 | __ | |oDate of Viva-voce|d2022-11-15 |
| 650 | __ | |aComputer Science and Applications|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aSepsis Prediction |
| 653 | __ | |aMachine Learning |
| 700 | __ | |aRao, Babu K|eGuide |
| 905 | __ | |anotification |
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