How can radiologists prepare for future of AI?

Yes, artificial intelligence (AI) will likely be a useful adjunct for radiologists...Read more on AuntMinnie.comRelated Reading: How will artificial intelligence enhance radiology? AI, radiomics help distinguish lung nodules on CT scans AI's role in radiology evolving toward a promising future Video from RSNA 2017: How will AI change radiology? Should radiologists and pathologists unite to master AI?
Source: AuntMinnie.com Headlines - Category: Radiology Source Type: news

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CONCLUSIONS: MLN enlargement predicts TFS and hospitalization risk in ILD, and is associated with decreased levels of a key circulating cytokine sCD40L. Incorporating MLN and cytokine findings into current prediction models might improve ILD prognostication. PMID: 30216085 [PubMed - as supplied by publisher]
Source: American Journal of Respiratory and Critical Care Medicine - Category: Respiratory Medicine Authors: Tags: Am J Respir Crit Care Med Source Type: research
We report herein three cases of major hepatectomy with IVC invasion and discuss several surgical tips.Patients and MethodsFrom March 2011 to February 2014, we retrospectively reviewed three cases of adrenal malignancy with liver and IVC invasion. Based on the severity of the malignant tumor, each case illustrates a different method to address surgical complications and maintain oncologic safety. Case 1: A 34-year-old woman was diagnosed with adrenocortical tumor during medical examination. Tumor invaded the right lobe of the liver and very close to the IVC. Fortunately, there was little thrombosis inside the IVC; we perfor...
Source: Annals of Surgical Oncology - Category: Cancer & Oncology Source Type: research
A group from Alabama has developed a deep-learning artificial intelligence...Read more on AuntMinnie.comRelated Reading: AI algorithm can triage head CT exams for urgent review NIH issues huge database of CT scans for AI testing SNMMI: AI can avoid patient misidentification on PET/CT Deep learning accurately detects brain hemorrhage AI can prescreen chest CT studies for pneumothorax
Source: AuntMinnie.com Headlines - Category: Radiology Source Type: news
Detecting lung nodules on CT scans is central to diagnosing cancer and the earlier that can be accomplished the better the outcome. Currently, only about two thirds of detectable nodules are actually spotted by trained professionals. Researchers at U...
Source: Medgadget - Category: Medical Devices Authors: Tags: Informatics Radiology Thoracic Surgery Source Type: blogs
As radiology artificial intelligence (AI) algorithms move toward clinical use,...Read more on AuntMinnie.comRelated Reading: New AI algorithm identifies small lung tumors on CT scans AI, new cardiac imaging technology can assess for CAD AI algorithm can triage head CT exams for urgent review AI characterizes complex mood disorders from fMRI 3 ways to ensure AI algorithms are really working
Source: AuntMinnie.com Headlines - Category: Radiology Source Type: news
Researchers from Florida have developed an artificial intelligence (AI) algorithm...Read more on AuntMinnie.comRelated Reading: AI, new cardiac imaging technology can assess for CAD AI algorithm can triage head CT exams for urgent review AI characterizes complex mood disorders from fMRI NIH issues huge database of CT scans for AI testing Deep learning accurately detects brain hemorrhage
Source: AuntMinnie.com Headlines - Category: Radiology Source Type: news
Intel (NSDQ:INTC) and Royal Philips (NYSE:PHG) said last week they are partnering to test Intel hardware’s ability to run deep learning artificial intelligence programs intended to improve the capabilities of Philips tech. The two companies joined to test the abilities of hardware using Intel Xeon processors and the OpenVINO toolkit for two AI-powered programs: one for bone-age-prediction modeling based on X-rays and one examining computed tomography scans of lungs for segmentation. Intel said that in the tests, the systems showed speed improvements of 188 times for the bone-age prediction model and 38 times for...
Source: Mass Device - Category: Medical Devices Authors: Tags: Business/Financial News Imaging Research & Development Software / IT Intel Corp. royalphilips Source Type: news
(University of Central Florida) Engineers at the University of Central Florida Center for Research in Computer Vision have taught a computer how to detect tiny specks of lung cancer in CT scans, which radiologists often have a difficult time identifying. The artificial intelligence system is about 95 percent accurate, compared to 65 percent when done by human eyes, the team said.
Source: EurekAlert! - Medicine and Health - Category: International Medicine & Public Health Source Type: news
Publication date: September 2018Source: Academic Radiology, Volume 25, Issue 9Author(s): Eduardo J. Mortani Barbosa, Maarten Lanclus, Wim Vos, Cedric Van Holsbeke, William De Backer, Jan De Backer, James LeeRationale and ObjectivesLong-term survival after lung transplantation (LTx) is limited by bronchiolitis obliterans syndrome (BOS), defined as a sustained decline in forced expiratory volume in the first second (FEV1) not explained by other causes. We assessed whether machine learning (ML) utilizing quantitative computed tomography (qCT) metrics can predict eventual development of BOS.Materials and MethodsPaired inspirat...
Source: Academic Radiology - Category: Radiology Source Type: research
Publication date: Available online 25 July 2018Source: European Journal of RadiologyAuthor(s): S. Dettmer, H. Suhling, I. Klingenberg, O. Otten, T. Kaireit, J. Fuge, J.M. Kuhnigk, J. Gottlieb, A. Haverich, T. Welte, F. Wacker, J. Vogel Claussen, H.O. ShinAbstractPurposeTo evaluate quantitative computed tomography (CT) measurements of the lung parenchyma in lung transplant (LTx) patients for early detection of the bronchiolitis obliterans syndrome (BOS).Materials and Methods359 CT scans of 122 lung transplant patients were evaluated. Measurements of lung volume and density were performed for the whole lung and separately fo...
Source: European Journal of Radiology - Category: Radiology Source Type: research
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