Results 151 to 160 of about 263,702 (262)

Diagnostic Accuracy of Size‐Based Preoperative CT Assessment for Predicting Lymph Node Metastasis in Colon Cancer: A Systematic Review and Meta‐Analysis

Annals of Gastroenterological Surgery, EarlyView.
Preoperative CT based on lymph node size shows moderate accuracy for detecting nodal metastasis in colon cancer. In this meta‐analysis of 29 studies (5,634 patients), pooled sensitivity and specificity were 0.69 and 0.66. Size‐based CT alone has limited value for clinical decision‐making.
Yuji Takayama, Tomoya Shimizu, Jun Watanabe, Shimpei Ogawa, Yukihide Kanemitsu   +4 more
wiley   +1 more source

On the Appropriate Classification of Discriminative Power Categories When Performing the Receiver Operating Characteristic Curve Analysis. [PDF]

Interdiscip Cardiovasc Thorac Surg
Nezic D.
europepmc   +1 more source

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

Annals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

A Reproducible MRI-Based Quantitative Feature for Differentiating Dysplastic Nodules from Hepatocellular Carcinoma: A Multicenter Retrospective Study. [PDF]

J Hepatocell Carcinoma
Zhang C, Xie S, Wang C, Ren T, Zhong X, Zhang Y, Li S, Wu W, Sun Y, Xie C.   +9 more
europepmc   +1 more source

Receiver operating characteristic (ROC) curve

, 2015
openaire   +1 more source

Lymphocyte‐C‐Reactive Protein Ratio as Promising New Marker for Predicting Surgical Site Infection in Children With Ulcerative Colitis

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Surgical site infection (SSI) is a major complication after ileal pouch–anal anastomosis (IPAA) in pediatric ulcerative colitis (UC), significantly impairing quality of life. The lymphocyte‐to–C‐reactive protein ratio (LCR), a composite marker of systemic inflammation and immune/nutritional status, has emerged as a potential ...
Yuhki Koike, Koki Higashi, Yuki Sato, Yuka Nagano, Tadanobu Shimura, Takahito Kitajima, Kohei Matsushita, Yoshiki Okita, Yoshinaga Okugawa, Yuji Toiyama   +9 more
wiley   +1 more source

Urinary DNA methylation biomarkers for bladder cancer diagnosis: a single center case-control study. [PDF]

Front Oncol
Li C, Fang R, Wang J, Wang Y, Zhao S, Wu Q, Ying C, Rao M.   +7 more
europepmc   +1 more source

Single‐Incision Laparoscopy‐First Strategy in Crohn's Disease: Risk Factors for Conversion and Surgical Outcomes

Annals of Gastroenterological Surgery, EarlyView.
In this retrospective study of 289 patients with Crohn's disease undergoing a single‐incision laparoscopy‐first (SILS‐first) strategy, conversion to open surgery was required in only 11.8% of cases. Fistula formation, colon resection, and smoking history were identified as independent risk factors for conversion, while postoperative complications and ...
Yuki Horio, Motoi Uchino, Yusuke Tomoo, Kentaro Nagano, Kurando Kusunoki, Ryuichi Kuwahara, Kei Kimura, Kozo Kataoka, Masataka Ikeda, Hiroki Ikeuchi   +9 more
wiley   +1 more source

Psychosocial Stress in the Chinese Community: Speech Analytics Through Linguistic and Acoustic Fusion Using Machine Learning. [PDF]

JMIR Biomed Eng
Chu AMY, Lam BSY, Tsang JTY, Tiwari A, Chan JNL, So MKP.   +5 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source