A product roll-out delay is the reason Cedara Software gave for its disappointing third quarter 2000 profits. The company's net loss was $119,000 (Canadian), compared to net income of $385,000 in the third quarter of 1999. Revenue for third
A product roll-out delay is the reason Cedara Software gave for its disappointing third quarter 2000 profits. The company's net loss was $119,000 (Canadian), compared to net income of $385,000 in the third quarter of 1999. Revenue for third quarter 2000 was $15.9 million, compared to $12.3 million for the same period a year earlier.
A new platform, the SNN 3.0, which integrates multiple surgical software systems, was not shipped to installed base customers until March 31, and was launched on the market immediately thereafter.
Cedara makes software for diagnostic imaging, image management, image-guided therapy, and cardiology. It recently released both Internet streaming software for medical imaging, called Cedara directDICOM, and Image Management Business for the PACS market.
Another factor affecting Cedara's earnings, according to a company statement, was losses for Surgical Navigation Specialists, in which Cedara has a minority interest. The company believes it will recover this loss from SNS profits in future quarters.
Cedara chairman and CEO Michael Greenberg said in a statement, "We have a backlog of orders for the SNN 3.0 platform. Despite the delay in shipping surgical systems, our R&D investment in growth markets is showing its potential."
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
MRI-Based AI Model Shows Promise in Predicting Lymph Node Metastasis with Breast Cancer
April 15th 2024For the prediction of axillary lymph node metastasis in patients with breast cancer, an MRI-based, 4D convolutional neural network model demonstrated an AUC of 87 percent and sensitivity of 89 percent, according to new research.