Results 211 to 220 of about 305,885 (348)

Antemortem dental records versus individual identification.

open access: yesJ Forensic Dent Sci, 2018
Thampan N   +5 more
europepmc   +1 more source

Dental radiographs in electronic medical records [PDF]

open access: yesBritish Dental Journal, 2019
Y, Hamrang-Yousefi, M, Pannu, J, Siddiqi
openaire   +2 more sources

Survival Outcomes of Gemcitabine–Cisplatin–S‐1 Versus Gemcitabine–Cisplatin in Unresectable Biliary Tract Cancer: A Multicenter Retrospective Study With a Focus on Conversion Surgery

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
In this multicenter retrospective study conducted by the Biliary Tract Club, we compared survival outcomes between gemcitabine–cisplatin–S‐1 (GCS) and gemcitabine–cisplatin (GC) in patients with unresectable biliary tract cancer, with a particular focus on conversion surgery. GCS was associated with longer overall and progression‐free survival compared
Hisashi Kosaka   +27 more
wiley   +1 more source

Rethinking Perioperative Corticosteroids in Esophageal Cancer Surgery: Evidence From an Integrative Meta‐Analysis

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Esophagectomy remains a highly invasive procedure associated with substantial postoperative morbidity. Pulmonary complications, anastomotic leakage, and in‐hospital mortality are of particular concern. Perioperative corticosteroids are often administered to attenuate excessive inflammatory responses; however, the clinical impact in ...
Tomohiko Yasuda   +4 more
wiley   +1 more source

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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

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