DIABETES PREDICTION USING SUPPORT VECTOR MACHINE AND GRADIENT DESCENT ALGORITHM

Diabetes is a health problem that can be deadly if not treated early.An early prediction of diabetes can prevent so many health problems in someones life.Using machine learning and algorithm to predict whether a person has diabetes or not can be the best solution when it comes to diabetes problems.Support Vector Machine can classify a data point into positive or negative value,it can help with predicting whether a person has diabetes or not using the diabetes factor that a person has.Using this factor Support Vector Machine can give value to the data point of a person and decided in which side of the margin it lies to,positive or negative value.The dataset itself contains 2000 patients with diabetes factor such as Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, Diabetes, and Age with Outcome as the predictor.The final results shown that Support Vector Machine is a good approach when it comes to predicting patients with diabetes.it shown a high accuracy score of 70% in accuracy,which means the Support Vector Machine model will most likely predict 7 out of 10 patients to be correct when it comes to Diabetes Disease.

Authors

Institutions

Publication Details

Journal
Proxies Jurnal Informatika
Published
2024-08-29
DOI
https://doi.org/10.24167/proxies.v8i1.12477
Citations
1
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DIABETES PREDICTION USING SUPPORT VECTOR MACHINE AND GRADIENT DESCENT ALGORITHM

Yonando Pratama B
1 citations
Proxies Jurnal Informatika
Artificial Intelligence in Healthcare
0.71
article

DIABETES PREDICTION USING SUPPORT VECTOR MACHINE AND GRADIENT DESCENT ALGORITHM

Yonando Pratama B
article en
1 citations

Abstract

Diabetes is a health problem that can be deadly if not treated early.An early prediction of diabetes can prevent so many health problems in someones life.Using machine learning and algorithm to predict whether a person has diabetes or not can be the best solution when it comes to diabetes problems.Support Vector Machine can classify a data point into positive or negative value,it can help with predicting whether a person has diabetes or not using the diabetes factor that a person has.Using this factor Support Vector Machine can give value to the data point of a person and decided in which side of the margin it lies to,positive or negative value.The dataset itself contains 2000 patients with diabetes factor such as Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, Diabetes, and Age with Outcome as the predictor.The final results shown that Support Vector Machine is a good approach when it comes to predicting patients with diabetes.it shown a high accuracy score of 70% in accuracy,which means the Support Vector Machine model will most likely predict 7 out of 10 patients to be correct when it comes to Diabetes Disease.

Proxies Jurnal InformatikaVol. 8(1)
Soegijapranata Catholic University (ID)
Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.