Results 241 to 250 of about 3,709,631 (405)

Simulation Devices in Interventional Radiology: Caveat Emptor [PDF]

, 2006
Derek Gould, Jim A. Reekers, David Kessel, N Chalmers, Marc Sapoval, Aalpen A. Patel, Gary J. Becker, Mick J. Lee, L Stockx   +8 more
openalex   +1 more source

As an Observer of Interventional Radiology [PDF]

Seminars in Interventional Radiology, 2018
openaire   +3 more sources

Radiation dose optimization in diagnostic and interventional radiology: Current issues and future perspectives.

Physica medica (Testo stampato), 2020
V. Tsapaki
semanticscholar   +1 more source

Empowering Biomedical Research with Foundation Models in Computational Microscopy: A Systematic Review

Advanced Intelligent Systems, EarlyView.
The integration of foundation models into computational microscopy revolutionizes biomedical research by enhancing imaging resolution, accelerating data analysis, and enabling real‐time biological interpretation. This systematic review critically examines recent advancements, highlights translational challenges, and discusses the transformative ...
Di Ding, Tianliang Yao, Genyi Feng, Xueqing Gao, Xusen Sun, Rong Luo   +5 more
wiley   +1 more source

Interventional Radiology in 2018: Training, Abilities and Critical Place in the Department of Radiology

Journal of the Belgian Society of Radiology, 2018
Otto van Delden
doaj   +1 more source

An Interventional Radiology Method for In Situ Assessments of Cancer Drug Response: Preclinical Development, Feasibility, and Safety. [PDF]

Radiol Imaging Cancer
Bhagavatula SK, Reichert R, Ahn SW, Foley G, Tatarova Z, Jakubik J, Dominas CA, Marlin C, Azzolini N, Maloney E, Martin S, Matthew D, Liu G, Panikkanvalappil S, Burch E, Epelboym Y, Hata N, Silverman SG, Jonas O.   +18 more
europepmc   +1 more source

Interventional Radiology in Cancer

, 2004
Andreas Adam, Robert F. Dondelinger, Peter R. Müeller   +2 more
openalex   +1 more source

Clinlabomics‐Enabled Blending Ensemble Learning for Low‐Cost Pan‐Cancer Detection and Classification Using Routine Clinical Laboratory Data

Advanced Intelligent Systems, EarlyView.
Researchers develop clinlabomics assisted for cancer identification, an artificial intelligence‐powered system using routine clinical lab data to detect and identify 10 cancer types. Tested on 19 199 individuals, it achieves 90.39% sensitivity and 82.41% specificity in cancer detection, with 72.57% accuracy in identifying specific cancer types ...
Bowen Zhang, Lin Li, Long Cheng, Yujie Liu, Zhaoqing Liu, Jiangpeng Wu, Pengyi Zhang, Jiarui Wang, Dekui Zhang, Shuyan Li   +9 more
wiley   +1 more source

Health‐related quality of life following total minimally invasive, hybrid minimally invasive or open oesophagectomy: a population‐based cohort study

BJS (British Journal of Surgery), EarlyView., 2020
All patients operated for oesophageal cancer in Sweden from 2013 to April 2018 were identified, and 246 patients were recruited to this population‐based nationwide Swedish study. The results show that longitudinal health‐related quality of life after minimally invasive oesophagectomy was similar to that of the open surgical approach.
F. Klevebro, J. H. Kauppila, S. Markar, A. Johar, P. Lagergren   +4 more
wiley   +1 more source

Exploring Interventional Radiology: A Multicentre Study on Saudi Medical and Radiology Technology Students' Perspectives. [PDF]

Adv Med Educ Pract
Aldahery S, Qwader R, Asiri RT, Al-Alfy A, Bushara L, Qurashi A, Alhazmi FH, Gareeballah A, Alahmadi AAS, Yousef M, Osman H, Alsharif W, Alshamrani KM.   +12 more
europepmc   +1 more source