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您的检索式：作者名="Marrium Anam"
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| 1 | Osteoporosis Prediction for Trabecular Bone using Machine Learning: A Review显示文摘Trabecular bone holds the utmost importance due to its significance regarding early bone loss.Diseases like osteoporosis greatly affect the structure of the Trabecular bone which results in different outcomes like high risk of fracture.The objective of this paper is to inspect the characteristics of the Trabecular Bone by using the Magnetic Resonance Imaging(MRI)technique.These characteristics prove to be quite helpful in studying different studies related to Trabecular bone such as osteoporosis.The things that were considered before the selection of the articles for the systematic review were language,research field,and electronic sources.Only those articles written in the English language were selected as it is the most prominent language used in scientific,engineering,computer science,and biomedical researches.This literature review was conducted on the articles published between 2006 and 2020.A total of 62 research papers out of 1050 papers were extracted which were according to our topic of review after screening abstract and article content for the title and abstract screening.The findings from those researches were compiled at the end of the result section.This systematic literature review presents a comprehensive report on scientific researches and studies that have been done in the medical area concerning trabecular bone. | Marrium Anam Vasaki a/p Ponnusamy Muzammil Hussain Muhammad Waqas Nadeem Mazhar Javed Hock Guan Goh Sadia Qadeer | 2021 | Computers, Materials & Continua2021，，4： | 0 |
| 2 | Hep-Pred: Hepatitis C Staging Prediction Using Fine Gaussian SVM显示文摘Hepatitis C is a contagious blood-borne infection,and it is mostly asymptomatic during the initial stages.Therefore,it is difficult to diagnose and treat patients in the early stages of infection.The disease’s progression to its last stages makes diagnosis and treatment more difficult.In this study,an AI system based on machine learning algorithms is presented to help healthcare professionals with an early diagnosis of hepatitis C.The dataset used for our Hep-Pred model is based on a literature study,and includes the records of 1385 patients infected with the hepatitis C virus.Patients in this dataset received treatment dosages for the hepatitis C virus for about 18 months.A former study divided the disease into four main stages.These stages have proven helpful for doctors to analyze the liver’s condition.The traditional way to check the staging is the biopsy,which is a painful and time-consuming process.This article aims to provide an effective and efficient approach to predict hepatitis C staging.For this purpose,the proposed technique uses a fine Gaussian SVM learning algorithm,providing 97.9%accurate results. | Taher M.Ghazal Marrium Anam Mohammad Kamrul Hasan Muzammil Hussain Muhammad Sajid Farooq Hafiz Muhammad Ammar Ali Munir Ahmad Tariq Rahim Soomro | 2021 | Computers, Materials & Continua2021，，10： | 0 |
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