AIMC Topic: Neoplasm Recurrence, Local

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Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repetitive liver injury. Surgical resection is generally selected as the radical cure treatment. Because the early recurrence of HCC after resection is as...

Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives.

Methods (San Diego, Calif.)
Radiation therapy is a pivotal cancer treatment that has significantly progressed over the last decade due to numerous technological breakthroughs. Imaging is now playing a critical role on deployment of the clinical workflow, both for treatment plan...

Robotic multivisceral pelvic resection: experience from an exenteration unit.

Techniques in coloproctology
BACKGROUND: Pelvic exenteration remains a viable and effective treatment option for the management of locally advanced or recurrent pelvic malignancy. The aim of this study was to present an early experience of robotic multivisceral resection of pelv...

A machine learning-based prognostic predictor for stage III colon cancer.

Scientific reports
Limited biomarkers have been identified as prognostic predictors for stage III colon cancer. To combat this shortfall, we developed a computer-aided approach which combing convolutional neural network with machine classifier to predict the prognosis ...

Histologic tissue components provide major cues for machine learning-based prostate cancer detection and grading on prostatectomy specimens.

Scientific reports
Automatically detecting and grading cancerous regions on radical prostatectomy (RP) sections facilitates graphical and quantitative pathology reporting, potentially benefitting post-surgery prognosis, recurrence prediction, and treatment planning aft...

Deep learning detection of prostate cancer recurrence with F-FACBC (fluciclovine, Axumin®) positron emission tomography.

European journal of nuclear medicine and molecular imaging
PURPOSE: To evaluate the performance of deep learning (DL) classifiers in discriminating normal and abnormal F-FACBC (fluciclovine, Axumin®) PET scans based on the presence of tumor recurrence and/or metastases in patients with prostate cancer (PC) a...

The use of artificial intelligence, machine learning and deep learning in oncologic histopathology.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
BACKGROUND: Recently, there has been a momentous drive to apply advanced artificial intelligence (AI) technologies to diagnostic medicine. The introduction of AI has provided vast new opportunities to improve health care and has introduced a new wave...

[Potential for improvement by new resection and imaging techniques in TUR-B].

Aktuelle Urologie
Transurethral resection of bladder tumors (TURB) is the cornerstone in urological care of bladder cancer patients. Since the introduction of resectoscopes almost 100 years ago, little has changed in the basic resection technique. The further dissemin...

A case-based ensemble learning system for explainable breast cancer recurrence prediction.

Artificial intelligence in medicine
Significant progress has been achieved in recent years in the application of artificial intelligence (AI) for medical decision support. However, many AI-based systems often only provide a final prediction to the doctor without an explanation of its u...