Results 141 to 150 of about 130,883 (345)

Diagnostic Accuracy of Deep Learning Models in Detecting Peri‐Implant Marginal Bone Loss: A Systematic Review and Meta‐Analysis

Clinical Oral Implants Research, EarlyView.
ABSTRACT Background Peri‐implantitis is a common implant complication requiring early detection to prevent bone loss and implant failure. Deep learning models show promise for enhancing radiographic diagnosis. Objectives This review systematically evaluated the diagnostic performance of deep learning models in detecting peri‐implant marginal bone loss ...
Momen A. Atieh, Maanas Shah, Abeer Hakam, Fawaghi AlAli, Samhar AlSayed, Andrew Tawse‐Smith, Nabeel H. M. Alsabeeha   +6 more
wiley   +1 more source

A Nomogram to Predict Long-Term Survival Outcomes of Patients Who Undergo Pneumonectomy for Non-small Cell Lung Cancer With Stage I-IIIB [PDF]

, 2021
Lei‐Lei Wu, Wutao Chen, Xuan Liu, Wenmei Jiang, Yang-Yu Huang, Peng Lin, Hao Long, Lanjun Zhang, Guowei Ma   +8 more
openalex   +1 more source

Endocrine Resistance Score Based on Three Key Genes Predicts Prognosis and Reveals Potential Therapeutic Targets for ER+HER2− Breast Cancer

Cell Proliferation, EarlyView.
We generated endocrine‐resistant BC cell lines and identified CLEC3A, PCDH10, and ST3GAL1 as key endocrine‐resistant genes. More importantly, we validated their role in mediating resistance through PI3K‐AKT signalling and developed a predictive ERS with strong clinical relevance.
Liqin Ping, Lewei Zhu, Nian Chen, Xikun Liu, Jirui Zhong, Xiaoqing Sun, Hailin Tang, Kaiming Zhang   +7 more
wiley   +1 more source

Development and validation of a nomogram to predict postoperative delirium in older patients after major abdominal surgery: a retrospective case-control study

Perioperative Medicine
Background Postoperative delirium is a common complication in older patients, with poor long-term outcomes. This study aimed to investigate risk factors and develop a predictive model for postoperative delirium in older patients after major abdominal ...
Yun-Gen Luo, Xiao-Dong Wu, Yu-Xiang Song, Xiao-Lin Wang, Kai Liu, Chun-Ting Shi, Zi-Lin Wang, Yu-Long Ma, Hao Li, Yan-Hong Liu, Wei-Dong Mi, Jing-Sheng Lou, Jiang-Bei Cao   +12 more
doaj   +1 more source

Mechanism of ITGB2 in Osteoclast Differentiation in Osteoarthritis

Cell Proliferation, EarlyView.
In osteoclast precursors, higher ITGB1 than ITGB2 expression increases ITGA2‐ITGB1 integrin. In OA, extracellular signals upregulate ITGB2 and downregulate ITGB1, enhancing ITGA2‐ITGB2 integrin. This activates Rac1 to Rac‐GTP, driving osteoclast differentiation. Hyperactive subchondral osteoclasts accelerate OA progression.
Yang Yang, Rui Sun, Zhibin Lan, Qi Ma, Gang Wu, Di Xue, Zhirong Chen, Yajing Su, Ye Ma, Xiaolei Chen, Jiangbo Yan, Long Ma, Xiaoxin He, Kuanmin Tian, Xiaoyi Ma, Xue Lin, Qunhua Jin   +16 more
wiley   +1 more source

The use of machine learning to predict pharmacological therapy in gestational diabetes: A scoping review

Diabetic Medicine, EarlyView.
Abstract Aims Early identification of pharmacological therapy for gestational diabetes mellitus (GDM), a common pregnancy complication, through machine learning could allow for better therapeutic strategies and improved treatment efficiency. This scoping review aimed to comprehensively review the machine learning models used to predict the need for ...
Jasmine R. Kirkwood, Natasha Galloway, Robert S. Lindsay, Areti Manataki, Deborah J. Wake, Rebecca M. Reynolds   +5 more
wiley   +1 more source

Prognostic models for all‐cause and cardiovascular mortality in type 2 diabetes: Systematic review

Diabetic Medicine, EarlyView.
Abstract Aims The elevated risk of all‐cause and cardiovascular mortality in individuals with type 2 diabetes mellitus (T2DM) has led to growing efforts to develop prognostic models for early identification of high‐risk individuals. This systematic review synthesised existing models to inform future model development, enhance predictive performance and
Monica Kundu, Mark P. Funnell, Zahra Karimi, Setor K. Kunutsor, Sara Naderpour, Arron Peace, Anneka Welford, Francesco Zaccardi, Kamlesh Khunti, Safoora Gharibzadeh, Ash Routen   +10 more
wiley   +1 more source

Tumor residue in patients with stage II–IVA nasopharyngeal carcinoma who received intensity-modulated radiation therapy: development and validation of a prediction nomogram integrating postradiotherapy plasma Epstein–Barr virus deoxyribonucleic acid, clinical stage, and radiotherapy dose [PDF]

, 2023
Yingying Huang, Jiayu Zhou, Ze‐Jiang Zhan, Liang‐Ru Ke, Wei‐Xiong Xia, Xun Cao, Zhuo‐Chen Cai, Ying Deng, Xi Chen, Lulu Zhang, Hao-yang Huang, Xiang Guo, Xing Lv   +12 more
openalex   +1 more source

Carotid Intima‐Media Thickness as a Marker of Subclinical Atherosclerosis in Adolescents With Severe Haemophilia

Haemophilia, EarlyView.
ABSTRACT Background The clinical focus of haemophilia has expanded beyond bleeding outcomes to encompass long‐term comorbidities such as cardiovascular disease (CVD). However, it remains unclear when vascular changes begin in this population. Carotid intima‐media thickness (cIMT), a validated, non‐invasive marker of subclinical atherosclerosis, may ...
Alyson Trillo, Juanita Hunter, Audrey Ofir, Jamie Shoag, Joanna A. Davis, Fernando F. Corrales‐Medina   +5 more
wiley   +1 more source

Exploring a Subpopulation of MASLD Associated With New Onset of CKD Using Supervised Clustering Techniques

Hepatology Research, EarlyView.
The supervised clustering of metabolic dysfunction‐associated steatotic liver disease (MASLD) using a SHapley Additive exPlanations (SHAP)‐converted matrix reveals distinct subpopulations that improved risk stratification for new onset of chronic kidney disease (CKD).
Itaru Hosaka, Marenao Tanaka, Tatsuya Sato, Yukinori Akiyama, Keitaro Nishizawa, Rie Matsumori, Hiroki Aida, Wataru Kawaharata, Kei Nakata, Koki Abe, Toru Suzuki, Hidemichi Kouzu, Naoya Yama, Nagisa Hanawa, Masato Furuhashi   +14 more
wiley   +1 more source