PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS' SYMPTOM DATA AND OVARY ULTRASOUND IMAGES /

Saved in:

Bibliographic Details
Main Author:	Suha, Sayma Alam
Corporate Author:	Supervised by Lt Col Muhammad Nazrul Islam (Assoc. Professor, Dept. of CSE, MIST.)
Format:	Book
Language:	English
Published:	Dhaka : CSE DEPT. MIST, c2022.
Subjects:	Computer Science and Engineering. This Thesis Paper of CSE in M.Sc. Program.
Tags:	Add Tag No Tags, Be the first to tag this record!

MARC


LEADER	00000nam a22000007a 4500
001	TP-2201
003	BD-DhMIS
005	20240429160229.0
008	240429t2022 bg a\|\|\|\| b\|\|\| 000 0 eng
040		\|a BD-DhMIS \|c BD-DhMIS
100		\|a Suha, Sayma Alam
245		\|a PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS' SYMPTOM DATA AND OVARY ULTRASOUND IMAGES / \|c Sayma Alam Suha
260		\|a Dhaka : \|b CSE DEPT. MIST, \|c c2022.
300		\|a xi, 120p. : \|b illus. ; \|c 29 cm.
504		\|a Includes bibliographical references.
541		\|e TP-2201
650		\|a Computer Science and Engineering.
650		\|a This Thesis Paper of CSE in M.Sc. Program.
710		\|a Supervised by Lt Col Muhammad Nazrul Islam \|e Assoc. Professor, Dept. of CSE, MIST.
942		\|2 ddc \|c TP
952		\|0 0 \|1 0 \|2 ddc \|4 0 \|6 2201_000000000000000_B_SC__CSE_2022 \|7 0 \|9 77789 \|a MISTCL \|b MISTCL \|d 2024-04-29 \|e Department of Computer Science and Engineering \|l 0 \|o 2201 B.Sc. CSE 2022 \|p TP-1010002201 \|r 2024-04-29 00:00:00 \|t 1 \|w 2024-04-29 \|y TP
999		\|c 11371 \|d 11371