Results 101 to 110 of about 172,138 (394)

Artificial Intelligence‐Assisted Urine Cytology for Noninvasive Detection of Muscle‐Invasive Urothelial Carcinoma: A Multi‐Center Diagnostic Study with Prospective Validation

Advanced Science, EarlyView.
Accurate preoperative detection of muscle‐invasive urothelial carcinoma (MIUC) is crucial for clinical decision‐making. This study developed PUCAS‐M, an artificial intelligence (AI) model that analyzes urine cytology to assist in differentiating MIUC from non‐MIUC.
Runnan Shen, Fan Jiang, Xiaowei Huang, Guibin Hong, Yun Luo, Huan Wan, Ye Xie, Mengyi Zhu, Yun Wang, Bohao Liu, Ping Qin, Yahui Wang, Haoxuan Wang, Hongkun Yang, Zhen Lin, Rui Chen, Nengtai Ouyang, Jian Huang, Tianxin Lin, Shaoxu Wu   +19 more
wiley   +1 more source

Development and Validation of a Nomogram for Predicting Overall Survival in Pancreatic NeuroendocrineTumors

Translational Oncology, 2018
BACKGROUND: The objective of current study was to develop and validate a nomogram to predict overall survival in pancreatic neuroendocrine tumors (PNETs).
Dong-liu Miao, Wei Song, Jun Qian, Zhi-gang Zhu, Qiong Wu, Chang-guang Lv, Lei Chen   +6 more
doaj   +1 more source

A machine learning model for distinguishing Kawasaki disease from sepsis

Scientific Reports, 2023
KD is an acute systemic vasculitis that most commonly affects children under 5 years old. Sepsis is a systemic inflammatory response syndrome caused by infection.
Chi Li, Yu-chen Liu, De-ran Zhang, Yan-xun Han, Bang-jie Chen, Yun Long, Cheng Wu   +6 more
doaj   +1 more source

Nomogram Based on Lactate Dehydrogenase-to-Albumin Ratio (LAR) and Platelet-to-Lymphocyte Ratio (PLR) for Predicting Survival in Nasopharyngeal Carcinoma

Journal of Inflammation Research, 2021
Purpose The prognosis of inflammation-related indicators like lactate dehydrogenase/albumin ratio (LAR) and the platelet/lymphocyte ratio (PLR) in nasopharyngeal carcinoma (NPC) is not yet clear.
Ru-Rong Peng, Zhongguo Liang, Kai-Hua Chen, Ling Li, S. Qu, Xiao-dong Zhu   +5 more
semanticscholar   +1 more source

Logistic Regression and Machine Learning Algorithms for the Risk Prediction of Perioperative Adverse Cardiovascular Events in Elderly Patients

AGING MEDICINE, EarlyView.
This manuscript focused on developing and validating prediction models for PACEs in elderly patients undergoing noncardiac surgery in China, utilizing routine laboratory examination findings. Logistic regression and machine learning algorithms were employed to construct these models.
Xiao Yan Li, Guang You Duan, Lin Li, Yi Yuan Gao, Li Wen Sun, Silin Zhu, Xiyezi Diao, Ning Wang, He Huang   +8 more
wiley   +1 more source

A wavelet features derived radiomics nomogram for prediction of malignant and benign early-stage lung nodules

Scientific Reports, 2021
This study was to develop a radiomics nomogram mainly using wavelet features for identifying malignant and benign early-stage lung nodules for high-risk screening.
Rui Jing, Jingtao Wang, Jiangbing Li, Xiaojuan Wang, Baijie Li, F. Xue, Guangrui Shao, Hao Xue   +7 more
semanticscholar   +1 more source

Developing a Clinician‐Friendly Online Dynamic Nomogram for Survival Prediction in Colon Cancer Patients

Annals of Gastroenterological Surgery, EarlyView.
This study developed a user‐friendly online dynamic nomogram using Bayesian model averaging to predict survival in colon cancer patients. Drawing on data from over 2400 cases, the model demonstrated strong predictive accuracy and was externally validated, offering a practical tool to support personalised clinical decision‐making.
Mohammad Asghari‐Jafarabadi, Simon Wilkins, John Paul Plazzer, Raymond Yap, Paul J. McMurrick   +4 more
wiley   +1 more source

Development and validation of a novel prognostic model for long-term overall survival in liposarcoma patients: a population-based study

Journal of International Medical Research, 2020
Objective To construct and validate a clinically accurate and histology-specific nomogram to predict overall survival (OS) among liposarcoma (LPS) patients.
Shuai Cao, Jie Li, Kai Yang, Jun Zhang, Jiawei Xu, Chaoshuai Feng, Haopeng Li   +6 more
doaj   +1 more source

Does shear wave ultrasound independently predict axillary lymph node metastasis in women with invasive breast cancer? [PDF]

, 2013
Shear wave elastography (SWE) shows promise as an adjunct to greyscale ultrasound examination in assessing breast masses. In breast cancer, higher lesion stiffness on SWE has been shown to be associated with features of poor prognosis.
A Evans, A Evans, AK Witkiewicz, Alastair Thompson, AM O’Shea, Andrew Evans, C Hatzis, CA Purdie, Caroline O. Michie, Colin A. Purdie, D Regner, DO Cosgrove, ES Burnside, J Boughey, JH Youk, JL Vandergrift, JLB Bevilacqua, JM Chang, Kim Thomson, KR Levental, LC Chen, Lee B. Jordan, MW Conklin, N Houssami, National Research Ethics Service, NO Kandemir, P Farmer, Patsy Whelehan, Petra Rauchhaus, PF Qiu, PL Fitzgibbons, Sarah Vinnicombe, T Kuehn, TC Kwok, WA Berg   +34 more
core   +4 more sources

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source