AI for Lung Cancer Diagnosis
The UK government recently announced a £21 million funding boost to 64 NHS trusts across England to roll out AI tools that can speed up the diagnosis and treatment of lung cancer.
Lung Cancer with an AI, National Library of Medicine
2023 Feb 19
National Library of Medicine
Lung Cancer with an AI
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954317/
" Always Good Lungs"
Using artificial intelligence to achieve early screening of lung cancer in 3 minutes?
Dian Nei Bioinformatics Co., Ltd. has developed a product that uses artificial intelligence for early screening of lung cancer - " Always Good Lungs ".
" Always Good Lungs " uses artificial intelligence engine screening to identify high-risk groups, so as to achieve early prevention and open the treatment window for advanced patients in advance.
The " Always Good Lungs " early screening method for lung cancer is very easy to operate. Open WeChat on your mobile phone and follow the WeChat official account of "Dian Nei Always Good Lungs ". According to the form, enter your age, height, weight, smoking history, family history, disease history, presence or absence of nodules and imaging characteristics of nodules, etc., through and Comparing a large database with more than one million cases around the world, you will get an early screening risk assessment in three minutes, giving you a copy of lung cancer risk value, causes and health advice and other practical information to help you with your future prevention and treatment work. It also provides professional advice and further medical professional consulting services.
" Always Good Lungs " integrates the current international mainstream lung cancer risk prediction model, and combines artificial intelligence and machine learning technology. After verification of 20,000 domestic lung cancer cases, it optimizes and forms a lung cancer intelligent screening engine "Lung Health" suitable for Chinese people.
Arterys –lung cancer (MRI, CT) diagnosis and MRI heart interpretation
Arterys receives FDA 510(k) for oncology imaging software
Feb 23, 2024
Arterys has announced that its Oncology AI imaging software has received 510(k) clearance from the U.S. Food and Drug Administration (FDA). The software suite is web-based, and assists radiologists and oncologists measure and track tumors or potential cancers. Its initial approved deep learning workflows ill be for liver computed tomography (CT) and magnetic resonance imaging (MRI) examinations and for lung CT scans.
Oncology AI is designed to assist radiologists by providing a simple web browser that helps them confirm, evaluate, quantify, and report on the presence or absence of lung nodules and liver lesions, along with their key characteristics. The software’s capabilities include single-click automated segmentation of lung nodules and liver lesions using deep learning and automated longitudinal tracking of nodules across multiple studies. It also provides intuitive LI-RADS workflow and score calculation. Oncology AI runs on the Arterys MICA (Medical Imaging Cloud AI) platform, which the San Francisco-headquartered company states is easier to deploy than on-premise imaging systems.
CAC-AI Analysis Technology and CT-AI Technology
Shengao Yunzhi's CAC-AI analysis technology for circulating abnormal cells has achieved ultra-high sensitivity detection of CAC cells in blood samples, reaching a detection sensitivity of 1/100,000. At the same time, the company has also developed CT-AI technology based on chest CT images. The two artificial intelligence technologies are jointly applied to complete the cytological identification and image identification of patients' pulmonary nodules. Combined with a complete data operation and management system, and finally confirmed by pathologists and imaging doctors, a comprehensive solution for early diagnosis of lung cancer patients was formed.
As an analysis tool for clinical pathologists, CAC-AI helps doctors realize AI judgment of pulmonary nodules at the cytological level through tumor liquid biopsy CAC detection technology. CAC detection technology was originated from MD Anderson Cancer Center in the United States. It targets four lung cancer-specific chromosomal variation regions to confirm the number of CAC in blood samples, and ultimately indicates the risk of benign and malignant lung nodules.
As an imaging consultant for clinicians, CT-AI can increase the detection rate, with a sensitivity of 96%; realize automatic nodule segmentation, measurement, type identification, tracking, follow-up and other functions to improve measurement accuracy; automatically analyze the characteristics of pulmonary nodules , accurately determine the nodule components, and perform auxiliary diagnosis of benign and malignant pulmonary nodules; it can also provide pulmonary nodule classification, lesion management opinions, and individualized clinical suggestions.
CAC-AI combined with CT-AI can provide multi-dimensional clinical evidence from imaging to cell chromosome variation, complement each other, and combine with the patient management system to comprehensively improve the accuracy and comprehensive diagnosis and treatment level of pulmonary nodules, and realize the diagnosis and treatment of pulmonary nodules. Assisted diagnosis of benign and malignant nodules and early detection of lung cancer.
"Full-Cycle Smart Solution for Lung Cancer"
The "full-cycle smart solution for lung cancer" achieves data unification and standardized management by building "imaging " and "clinical" data centers for medical institutions, improving data availability and security; and ultimately provides AI through the AI medical application platform, a full-cycle, standardized lung cancer solution for prevention, diagnosis, and treatment.
red dot®, an algorithm from BeholdAI
red dot® can identify suspected lung cancer in chest X-rays to increase the numbers of cancers diagnosed and reduce the time patients wait for scans
red dot® is the award-winning, artificially intelligent CT and X-Ray medical diagnosis platform that can almost instantly detect various conditions, such as lung cancer and stroke, and has shown proven results in the UK and globally (FDA and CE approved).
Using their red dot algorithm based on deep learning models, Behold.ai’s software is able to classify a CXR and localize its findings as heatmaps. Their AI was trained from over 30,000 images, all of which had been reviewed by experienced UK-certified Consultant Radiologists. This resulted in an algorithm with over 90% accuracy that is able to detect abnormalities within seconds.
The company, headquartered in London, is already collaborating with the NHS and has deployed its AI solution in several NHS Trusts. Behold.ai has even achieved the gold standard of quality certification for ‘Instant Triage’ Solution.
In June 2022 the company entered a partnership with NHS Somerset to test Behold’s AI algorithm in diagnosing lung cancers.
Behold.AI Technologies Ltd
https://behold.ai/
qXR software from Qure.ai
Qure.ai Technologies Private limited
qXR
AI for Blazing Fast Reporting on Chest X-Rays
World’s most widely used AI for comprehensive chest X-ray reporting. Pre-read assistance in 20 seconds with findings across lung, heart, pleura, mediastinum, bones & diaphragm.
90% of the missed/mislabeled CXR have been identified with a critical abnormality by qXR with zero false positives
https://www.qure.ai/product/qxr
“Sybil” - MIT’s AI tool can predict lung cancer risk up to six years in advance
Using a single low-dose chest scan, the AI model “Sybil” can predict the risk of lung cancers occurring 1-6 years after a screening.
Virtual Nodule Clinic (VNC), developed by Optellum
Optellum Ltd
https://optellum.com/
https://optellum.com/products-and-solutions/lung-cancer-prediction-ai/
https://optellum.com/2022/08/how-optellum-is-working-to-change-the-survival-rates-for-lung-cancer-with-an-innovative-ai-platform/
Optellum’s Lung Cancer Prediction artificial intelligence solution
Optellum® Virtual Nodule Clinic Lung Cancer Prediction helps pulmonologists with optimal clinical decisions driving earlier cancer treatment and fewer invasive procedures on benign nodules.
All patients are automatically added to a dashboard of patients ready for enrollment and follow-ups, securely accessible through a web browser from any computer
Users can review relevant patient information in one view and track pulmonary nodules longitudinally
Enables easy navigation and display of current and prior CT scans and reports with the patient timeline
Virtual Nodule Clinic also provides more tools for optimal patient care, read more about its other functions.