AIMC Topic: Neoplasm Recurrence, Local

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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...

Vessel and Tension-Free Reconstruction During Robot-Assisted Partial Nephrectomy for Hilar Tumors: "Garland" Technique and Midterm Outcomes.

Journal of endourology
Robot-assisted partial nephrectomy (RAPN) is increasingly applied to renal hilar tumors. The present study aims to introduce our vessel and tension-free reconstruction technique and discuss the perioperative, functional, and midterm oncologic outcom...

Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Between 30%-40% of patients with prostate cancer experience disease recurrence following radical prostatectomy. Existing clinical models for recurrence risk prediction do not account for population-based variation in the tumor phenotype, des...

Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumours affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) wit...

CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.

European radiology
PURPOSE: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. The aims of this study are to develop and validate a computed tomography ...