» Authors » Mayidili Nijiati

Mayidili Nijiati

Explore the profile of Mayidili Nijiati including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 15
Citations 66
Followers 0
Related Specialties
Top 10 Co-Authors
Published In
Affiliations
Soon will be listed here.
Recent Articles
1.
Fan S, Abulizi A, You Y, Huang C, Yimit Y, Li Q, et al.
BMC Infect Dis . 2024 Aug; 24(1):875. PMID: 39198742
Background: Pulmonary tuberculosis (PTB) is a prevalent chronic disease associated with a significant economic burden on patients. Using machine learning to predict hospitalization costs can allocate medical resources effectively and...
2.
Nijiati M, Tuerdi M, Damola M, Yimit Y, Yang J, Abulaiti A, et al.
Front Physiol . 2024 Aug; 15:1426468. PMID: 39175611
Hepatic cystic echinococcosis (HCE) is a widely seen parasitic infection. Biological activity is crucial for treatment planning. This work aims to explore the potential applications of a deep learning radiomics...
3.
Yasin P, Yimit Y, Cai X, Aimaiti A, Sheng W, Mamat M, et al.
Eur J Med Res . 2024 Jul; 29(1):383. PMID: 39054495
Background: Tuberculosis spondylitis (TS), commonly known as Pott's disease, is a severe type of skeletal tuberculosis that typically requires surgical treatment. However, this treatment option has led to an increase...
4.
Yimit Y, Yasin P, Tuersun A, Wang J, Wang X, Huang C, et al.
Acad Radiol . 2024 Mar; 31(8):3384-3396. PMID: 38508934
Rationale And Objectives: Medulloblastoma (MB) and Ependymoma (EM) in children, share similarities in age group, tumor location, and clinical presentation. Distinguishing between them through clinical diagnosis is challenging. This study...
5.
Yimit Y, Yasin P, Tuersun A, Abulizi A, Jia W, Wang Y, et al.
Eur J Med Res . 2023 Dec; 28(1):577. PMID: 38071384
Background: Cerebral alveolar echinococcosis (CAE) and brain metastases (BM) share similar in locations and imaging appearance. However, they require distinct treatment approaches, with CAE typically treated with chemotherapy and surgery,...
6.
Nijiati M, Guo L, Tuersun A, Damola M, Abulizi A, Dong J, et al.
iScience . 2023 Nov; 26(11):108326. PMID: 37965132
Three deep learning (DL)-based prediction models (PMs) using longitudinal CT images were developed to predict tuberculosis (TB) treatment outcomes. The internal dataset consists of 493 bacteriologically confirmed TB patients who...
7.
Nijiati M, Guo L, Abulizi A, Fan S, Wubuli A, Tuersun A, et al.
Eur J Radiol . 2023 Nov; 169:111180. PMID: 37949023
Background: To predict tuberculosis (TB) treatment outcomes at an early stage, prevent poor outcomes ofdrug-resistant tuberculosis(DR-TB) and interrupt transmission. Methods: An internal cohort for model development consists of 204 bacteriologically-confirmed...
8.
Nijiati M, Zhou R, Damaola M, Hu C, Li L, Qian B, et al.
Front Mol Biosci . 2022 Dec; 9:1086047. PMID: 36545511
Active pulmonary tuberculosis (ATB), which is more infectious and has a higher mortality rate compared with non-active pulmonary tuberculosis (non-ATB), needs to be diagnosed accurately and timely to prevent the...
9.
Nijiati M, Tuersun A, Zhang Y, Yuan Q, Gong P, Abulizi A, et al.
Front Physiol . 2022 Dec; 13:977427. PMID: 36505076
Accurate localization and classification of intracerebral hemorrhage (ICH) lesions are of great significance for the treatment and prognosis of patients with ICH. The purpose of this study is to develop...
10.
Nijiati M, Aihaiti D, Huojia A, Abulizi A, Mutailifu S, Rouzi N, et al.
Front Oncol . 2022 Jun; 12:876624. PMID: 35734595
Objective: Preoperative identification of lymphovascular invasion (LVI) in patients with invasive breast cancer is challenging due to absence of reliable biomarkers or tools in clinical settings. We aimed to establish...