Aidoc partners with SaferMD on AI for MIPS reporting

AuntMinnie.com staff writers
Nov 18, 2018

Israeli artificial intelligence (AI) software developer Aidoc and SaferMD have developed AI software that can automatically generate the data radiologists need to comply with reporting in the Medicare Merit-Based Incentive Payment System (MIPS).

SaferMD's Qualified Clinical Data Registry (QCDR) for radiology includes 19 high-priority measures and eight submeasures for imaging exams. It has received approval from the U.S. Centers for Medicare and Medicaid Services (CMS) for 2018-2019 MIPS reporting. Integrating this registry into Aidoc's AI software for flagging critical patient conditions may help improve patient care and financial returns, according to Aidoc.

Aidoc and SaferMD will demonstrate their combined software at the upcoming RSNA 2018 meeting in Chicago.

Latest in Artificial Intelligence
Ultrasound Scanner Ultraviolet 400
Deep-learning algorithm improves liver fibrosis diagnosis
April 23, 2024
Chat Gpt Artificial Intelligence Ai Head
NLP uncovers racial bias in documenting ob/gyn imaging findings
April 23, 2024
Stroke Skull Xray 400
Can ChatGPT ‘data mine’ patient reports for stroke registries?
April 19, 2024
Ai Handshake
Blackford and Lucida Medical partner on prostate cancer imaging
April 17, 2024
Related Stories
2018 06 06 00 59 2262 Quality 400
Industry News
MSN touts 3 new MIPS radiology quality measures
2015 08 31 14 32 34 386 Gale Brian 175
IS
SaferMD helps radiologists reduce malpractice risk
2017 03 09 14 05 24 948 Chest Lung Xray 400
Artificial Intelligence
Canada-U.S. duo wins RSNA pneumonia AI challenge
2016 10 03 14 26 17 320 Computer Binary 400
Artificial Intelligence
Are medical students avoiding radiology because of AI?
More in Artificial Intelligence
Deep-learning algorithm improves liver fibrosis diagnosis
By Amerigo Allegretto
An algorithm combining the Fibrosis-4 Index and an ultrasound deep-learning model could improve diagnostic accuracy for advanced liver fibrosis.
April 23, 2024
Ultrasound Scanner Ultraviolet 400
NLP uncovers racial bias in documenting ob/gyn imaging findings
By Amerigo Allegretto
Natural language processing (NLP), a form of AI, can uncover racial bias in documenting radiology-confirmed ob/gyn findings.
April 23, 2024
Chat Gpt Artificial Intelligence Ai Head
Can ChatGPT ‘data mine’ patient reports for stroke registries?
By Will Morton
ChatGPT-4 appears useful for extracting details from reports on thrombectomy procedures in stroke patients, a labor-intensive and error-prone task currently performed by human readers.
April 19, 2024
Stroke Skull Xray 400
Blackford and Lucida Medical partner on prostate cancer imaging
By AuntMinnie.com staff writers
Blackford has entered a commercial partnership with Lucida Medical to integrate Lucida's prostate cancer MRI imaging software (Pi) into its AI platform.
April 17, 2024
Ai Handshake
CT-based deep learning identifies patients at further lung cancer risk
By Kate Madden Yee
A CT-based deep learning model can identify individuals with clinical stage IA non-small cell lung cancer (NSCLC) at high risk of further disease, researchers have found.
April 16, 2024
Ai
Deep-learning model determines breast tumor staging
By Amerigo Allegretto
A deep-learning model based on mammographic images can determine tumor staging and sentinel lymph node metastasis in breast cancer patients.
April 16, 2024
Researchers explain the data preparation and structure of a proposed CNN-based deep learning model using mammography features to determine breast tumor staging. The image is available for use under a Creative Commons license: CC BY-NC-ND 4.0 DEED Attribution-NonCommercial-NoDerivs 4.0 International.
16 Bit gets FDA nod for AI x-ray software
By AuntMinnie.com staff writers
Canadian AI software developer 16 Bit has received de novo approval from the U.S. Food and Drug Administration (FDA) for Rho, an AI tool for evaluating low bone mineral density.
April 12, 2024
Bmd
Vision transformer AI model boosts PET/CT imaging of cancer
By Will Morton
A vision transformer AI model outperformed convolutional neural networks when classifying tumors on PET/CT images as benign or malignant.
April 12, 2024
Predictions and Grad-CAMs of ViT-based models on sample PET/CT, PET, and CT test images from the “positive” class. ViT was fine-tuned using training data for each modality. The bounding boxes depicted in the figure indicate malignant lesions. The top row of the Grad-CAMs shows important areas for “positive” predictions, and the bottom row shows areas for “negative” predictions. Image courtesy of Scientific Reports.
UltraCon: Machine learning predicts sonographer burnout
By Amerigo Allegretto
Machine-learning approaches can predict burnout among sonographers, though established burnout indices may be enough, according to research presented April 9 at UltraCon.
April 9, 2024
Jennifer Bagley from the University of Oklahoma presents findings at UltraCon on the performance of two machine learning approaches in predicting burnout among sonographers.
AI helps select patients for supplemental breast cancer screening
By Erik L. Ridley
An AI-based method can outperform breast density measurements for flagging patients who would benefit from supplemental breast cancer screening.
April 9, 2024
Breast Cancer 3 D
AI model predicts invasiveness of lung cancer on CT scans
By Will Morton
Radiologists in Beijing, China, have developed a joint deep-learning and radiomics AI model that can flag how invasive tumors may be in patients with lung cancer.
April 9, 2024
Lung Ai
Can AI improve sustainability in nuclear medicine?
Nuclear medicine experts support the use of AI to improve sustainability of practices in the field, yet say implementation will require careful consideration of the technology’s benefits and detriments.
April 9, 2024
ChatGPT powered by GPT-4 and using DALL-E−3 was asked to generate an image for teaching purposes that demonstrated: a nuclear medicine bone scan with skeletal metastases (top left); coronary artery disease (top right); an F-18 FDG-PET scan of the brain with Alzheimer's disease (bottom left); and an x-ray showing a fracture (bottom right). These are misleading for educational purposes and for patients who may be searching for information. Image and caption courtesy of Radiography.
Page 1 of 365
Next Page