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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...

Radiomics and deep learning in lung cancer.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Lung malignancies have been extensively characterized through radiomics and deep learning. By providing a three-dimensional characterization of the lesion, models based on radiomic features from computed tomography (CT) and positron-emission tomograp...

Triple-Negative Breast Cancer: A Review of Conventional and Advanced Therapeutic Strategies.

International journal of environmental research and public health
Triple-negative breast cancer (TNBC) cells are deficient in estrogen, progesterone and ERBB2 receptor expression, presenting a particularly challenging therapeutic target due to their highly invasive nature and relatively low response to therapeutics...

Machine Learning techniques in breast cancer prognosis prediction: A primary evaluation.

Cancer medicine
More than 750 000 women in Italy are surviving a diagnosis of breast cancer. A large body of literature tells us which characteristics impact the most on their prognosis. However, the prediction of each disease course and then the establishment of a ...

Identification of a novel gene signature for the prediction of recurrence in HCC patients by machine learning of genome-wide databases.

Scientific reports
Hepatocellular carcinoma (HCC) is a common malignant tumor in China. In the present study, we aimed to construct and verify a prediction model of recurrence in HCC patients using databases (TCGA, AMC and Inserm) and machine learning methods and obtai...