To predict treatment outcomes more accurately for individual patients, and truly realize the full value of AI and machine learning in the oncology sector, providers need AI solutions that can learn from huge volumes of real-time data from patients, oncologists and cancer centers. At Elekta, we ...
Now, let’s investigate some practical applications of artificial intelligence in cancer prediction, diagnosis, treatment, and research. How AI is applied in cancer prediction 1. Using AI in cancer prediction with medical data and imaging Artificial intelligence can not only detect existing ca...
the most common manifestation of liver cancer,impactsmore than 800,000 people yearly and causes nearly as many deaths. The hope was to develop a new treatment pathway and a “novel hit molecule” that could take advantage of that pathway. The AI did precisely that—and it only took 30 days...
Additionally, AI’s impact has extended to optimizing clinical trials and refining patient recruitment through alignment with trial criteria. Notably, precision medicine has become a worldwide trend. Precision medicine refers to a medical treatment selection process by which the most appropriate treatment ...
AI systems can predict which patients are more likely to benefit from immunotherapy, potentially sparing others from the side effects and costs of ineffective treatments. With its ability to synthesize large datasets and identify meaningful patterns, AI is helping make treatment choices more data-driven...
AI algorithms are routinely utilized in methodologies involved in diagnosis, prognosis, and treatment determinations for patients with cancer. Studies published this year established potential roles for AI-supported mammography to increase breast cancer detection rates; however, there is much wor...
The framework was tested using synthetic data, and the model successfully recommended optimal treatment strategies with high accuracy. “This work presents a new mathematical framework that depicts a new way of modeling cancer heterogeneities by using different interaction laws and asses...
Cancer is associated with significant morbimortality globally. Advances in screening, diagnosis, management and survivorship were substantial in the last decades, however, challenges in providing personalized and data-oriented care remain. Artificial intelligence (AI), a branch of computer science ...
Dr Shao Zhimin , from Shanghai Cancer Center, teamed up with experts in other fields of medicine, brain science, and information technology to come up with an intelligent plan for triple-negative breast cancer diagnosis. "Cli...
Given Brainomix's success in developing imaging biomarkers for Stroke and Interstitial Lung Disease (ILD), future research and development will expand the Brainomix 360 platform to include a Cancer solution, with a focus on improving treatment response assessment in Oncology. ...