Engineers develop A.I. System to detect often-missed cancer tumors

(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

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Harvard researchers have developed an artificial intelligence (AI) algorithm...Read more on AuntMinnie.comRelated Reading: AI malware deceives radiologists with fake tumors on CT AI reliably characterizes pulmonary nodules on CT AI spots lung nodules on CT, with low false-positive rate New AI algorithm identifies small lung tumors on CT scans NIH issues huge database of CT scans for AI testing
Source: AuntMinnie.com Headlines - Category: Radiology Source Type: news
How do you create a smart algorithm? Where and how do you get the data for it? What do you need for a pattern recognizing program to work well and what are the challenges? Nowadays, everyone seems to be building artificial intelligence-based software, also in healthcare, but no one talks about one of the most important aspects of the work: data annotation and the people who are undertaking this time-consuming, rather monotonous task without the flare that usually encircles A.I. Without their dedicated work, it is impossible to develop algorithms, so we thought it is time to sing an ode to the superheroes of algorithm devel...
Source: The Medical Futurist - Category: Information Technology Authors: Tags: Artificial Intelligence in Medicine Future of Medicine AI algorithm annotation data data annotation doctor Health Healthcare physician smart algorithm technology Source Type: blogs
This study had a retrospective multicenter (two hospitals in China) design and a radiomic analysis was performed using contrast enhanced CT in advanced HGSOC (FIGO stage III or IV) patients. We used a minimum 18-month follow-up period for all patients (median 38.8 months, range 18.8–81.8 months). All patients were divided into three cohorts according to the timing of their surgery and hospital stay: training cohort (TC) and internal validation cohort (IVC) were from one hospital, and independent external validation cohort (IEVC) was from another hospital. A total of 620 3-D radiomic features were extracted and a Lass...
Source: Frontiers in Oncology - Category: Cancer & Oncology Source Type: research
Rayfield Byrd knows when it’s time to wake up every morning. The 68-year-old Oakland, Cal., resident hears a voice from the living room offering a cheery good morning. Except Byrd lives alone. A little after 8 a.m. each day, a small yellow robot named Mabu asks Byrd how he’s doing. Byrd has Type 2 diabetes and congestive heart failure, and about three years ago, he had surgery to implant a microvalve in his heart to keep his blood flowing properly. To stay healthy, he takes four medications a day and needs to exercise regularly. To make sure his heart is still pumping effectively, his doctor needs to stay on to...
Source: TIME: Health - Category: Consumer Health News Authors: Tags: Uncategorized Artificial Intelligence Life Reinvented medicine Source Type: news
If you follow the recent advances in medical technology and artificial intelligence, you may have heard people make bold claims that AI will replace tomorrow’s doctors. While there are still ways to go for technology to reach these sci-fi level...
Source: Medgadget - Category: Medical Devices Authors: Tags: Exclusive Informatics Radiology Source Type: blogs
Conclusion: Study reveals a high prevalance of potentially treatable extra pulmonary and pulmonary comorbidities. We recommend a list of these treatable comorbidities be included as part of the standard work up of COPD patients undergoing CT as it would enable better patient outcomes.
Source: European Respiratory Journal - Category: Respiratory Medicine Authors: Tags: Clinical Problems Source Type: research
We report a case of Paragonimus westermani infection simultaneously affecting two separate organs that presented as both a pulmonary cavity and adrenal mass in an immunocompromised host.A 65-year-old male with a previous kidney transplant visited our clinic because of hemoptysis. Forty-three months earlier, bilateral spontaneous pneumothorax was diagnosed and treated with oxygen supplementation and right chest tube insertion. At that time, there was no demonstrable cavitary lesion in either lung and no mass in the adrenal glands (Fig. 1A, 1B). Computed tomography (CT) of the chest when the patient presented with hemoptysis...
Source: European Respiratory Journal - Category: Respiratory Medicine Authors: Tags: Respiratory infections Source Type: research
Lung cancer is the most frequent type of cancer across genders and the most common reason for cancer-related death worldwide [1]. Hybrid positron emission tomography/computed tomography (PET/CT) using 18F-fluorodeoxyglucose (FDG) is an established imaging method for the staging of patients with lung cancer [2]. Recently, the use of artificial intelligence and more specifically deep learning has produced promising results in various applications in medicine, including automated skin cancer detection [3] or automated Alzheimer disease detection based on FDG-PET data [4].
Source: Lung Cancer - Category: Cancer & Oncology Authors: Source Type: research
Lung cancer is the most frequent type of cancer across genders and the most common reason for cancer-related death worldwide [1]. Hybrid positron emission tomography/computed tomography (PET/CT) using 18F-fluorodeoxyglucose (FDG) is an established imaging method for the staging of patients with lung cancer [2]. Recently, the use of artificial intelligence and more specifically deep learning has produced promising results in various applications in medicine, including automated skin cancer detection [3] or automated Alzheimer disease detection based on FDG-PET data [4].
Source: Lung Cancer - Category: Cancer & Oncology Authors: Source Type: research
Physicians may soon use artificial intelligence (AI) and medical images to study tumors without a biopsy. The techniques developed to study tumors in this new way are described in the September 1 issue of The Lancet Oncology. Along with helping physicians learn more about tumors without surgery, the new approach should help identify which cancer patients will respond best to cutting-edge immunotherapy treatments. The AI techniques could be useful for “predicting clinical outcomes of patients treated with immunotherapy when validated by further prospective randomized trials,” the authors wrote. Immunotherapy tre...
Source: Asbestos and Mesothelioma News - Category: Environmental Health Authors: Source Type: news
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