Using NGS data from 36,445 tumor samples ... A certified oncologist manually reviewed patients’ charts to see whether they were treated according to the OncoNPC cancer type predictions. The ...

Along with the prediction score for relapse, models also return an accompanying chart or ... In conclusion, we use tabular and graph machine learning for objective and reproducible early-stage NSCLC ...

The team developed this machine ... using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions ...

Predicting the course of prostate cancer is challenging because only a fraction of prostate cancer patients experience recurrence after radical prostatectomy or radiation therapy. Yet, prostate ...

Artificial intelligence (AI) and machine learning techniques show promise for improving cancer pain prediction and management ... to systematically review the use of AI/machine learning algorithms ...

Findings from the new study—published today in Scientific Reports through an article titled “Objective risk stratification of prostate cancer using machine learning and radiomics applied to ...

Selection of appropriate adjuvant therapy to ultimately reduce the risk of breast cancer (BC) recurrence is a challenge for medical oncologists. Several automated risk prediction models have been ...