paper-with-me

홈 › Papers

Development of a Machine Learning Model and Mobile Application to Aid in Predicting Dosage of Vitamin K Antagonists Among Indian Patients

2020-04-19 · Amruthlal M, Devika S, Ameer Suhail P A, Aravind K Menon, Vignesh Krishnan, Alan Thomas, Manu Thomas, Sanjay G, Lakshmi Kanth L R, Jimmy Jose, Harikrishnan S

Patients who undergo mechanical heart valve replacements or have conditions like Atrial Fibrillation have to take Vitamin K Antagonists (VKA) drugs to prevent coagulation of blood. These drugs have narrow therapeutic range and need to be very closely monitored due to life threatening side effects. The dosage of VKA drug is determined and revised by a physician based on Prothrombin Time - International Normalised Ratio (PT-INR) value obtained through a blood test. Our work aimed at predicting the maintenance dosage of warfarin, the present most widely recommended anticoagulant drug, using the de-identified medical data collected from 109 patients from Kerala. A Support Vector Machine (SVM) Regression model was built to predict the maintenance dosage of warfarin, for patients who have been undergoing treatment from a physician and have reached stable INR values between 2.0 and 4.0.

📄 PDF Abstract BibTeX arXiv:2004.11460

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Predicting Dosage of Immunosuppressant Drugs After Kidney Transplantation Using Machine Learning

2023-08-22 · Kapil Panda, Anirudh Mazumder

While kidney transplants are seen as the best treatment option for patients with end-stage renal disease and kidney failure, the organ's health depends on the dosage of immunosuppressant drugs post-transplantation. Due t…

Machine Learning Method Used to find Discrete and Predictive Treatment of Cancer

2020-04-21 · SeyedMehdi Abtahi, Mojtaba Sharifi

Cancer is one of the most common diseases worldwide, posing a serious threat to human health and leading to the deaths of a large number of people. It was observed during the drug administration in chemotherapy that immu…

BIG-bench Machine LearningDecision Making

Spectroscopy Approaches for Food Safety Applications: Improving Data Efficiency Using Active Learning and Semi-Supervised Learning

2021-10-07 · Huanle Zhang, Nicharee Wisuthiphaet, Hemiao Cui, Nitin Nitin 외

The past decade witnesses a rapid development in the measurement and monitoring technologies for food science. Among these technologies, spectroscopy has been widely used for the analysis of food quality, safety, and nut…

Active Learning

Mobile big data analysis with machine learning

2018-08-02 · Jiyang Xie, Zeyu Song, Yupeng Li, Zhanyu Ma

This paper investigates to identify the requirement and the development of machine learning-based mobile big data analysis through discussing the insights of challenges in the mobile big data (MBD). Furthermore, it revie…

BIG-bench Machine Learningspeech-recognitionSpeech Recognition

A Deep Neural Network -- Mechanistic Hybrid Model to Predict Pharmacokinetics in Rat

2023-10-13 · Florian Führer, Andrea Gruber, Holger Diedam, Andreas H. Göller 외

An important aspect in the development of small molecules as drugs or agro-chemicals is their systemic availability after intravenous and oral administration. The prediction of the systemic availability from the chemical…