AI Medical Compendium Journal:
European journal of cancer (Oxford, England : 1990)

Showing 11 to 20 of 58 articles

Predicting benefit from PARP inhibitors using deep learning on H&E-stained ovarian cancer slides.

European journal of cancer (Oxford, England : 1990)
PURPOSE: Ovarian cancer patients with a Homologous Recombination Deficiency (HRD) often benefit from polyadenosine diphosphate-ribose polymerase (PARP) inhibitor maintenance therapy after response to platinum-based chemotherapy. HR status is currentl...

Computerizing the first step of the two-step algorithm in dermoscopy: A convolutional neural network for differentiating melanocytic from non-melanocytic skin lesions.

European journal of cancer (Oxford, England : 1990)
IMPORTANCE: Convolutional neural networks (CNN) have shown performance equal to trained dermatologists in differentiating benign from malignant skin lesions. To improve clinicians' management decisions, additional classifications into diagnostic cate...

Artificial intelligence breakthroughs in pioneering early diagnosis and precision treatment of breast cancer: A multimethod study.

European journal of cancer (Oxford, England : 1990)
This article delves into the potential of artificial intelligence (AI) to enhance early breast cancer (BC) detection for improved treatment outcomes and patient care. Utilizing a multimethod approach comprising literature review and experiments, the ...

Prediction of prognosis and treatment response in ovarian cancer patients from histopathology images using graph deep learning: a multicenter retrospective study.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Ovarian cancer (OV) is a prevalent and deadly disease with high mortality rates. The development of accurate prognostic tools and personalized therapeutic strategies is crucial for improving patient outcomes.

Advancing equitable and personalized cancer care: Novel applications and priorities of artificial intelligence for fairness and inclusivity in the patient care workflow.

European journal of cancer (Oxford, England : 1990)
Patient care workflows are highly multimodal and intertwined: the intersection of data outputs provided from different disciplines and in different formats remains one of the main challenges of modern oncology. Artificial Intelligence (AI) has the po...

Deep learning based histological classification of adnex tumors.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Cutaneous adnexal tumors are a diverse group of tumors arising from structures of the hair appendages. Although often benign, malignant entities occur which can metastasize and lead to patients´ death. Correct diagnosis is critical to ens...

Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Sentinel lymph node (SLN) status is a clinically important prognostic biomarker in breast cancer and is used to guide therapy, especially for hormone receptor-positive, HER2-negative cases. However, invasive lymph node staging is increasi...

Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study.

European journal of cancer (Oxford, England : 1990)
AIM: Gastric cancer (GC) is a tumour entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesised that GC primary tissue contains information that is predictive of lymph node status and patient pro...

Transcriptional intra-tumour heterogeneity predicted by deep learning in routine breast histopathology slides provides independent prognostic information.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Intra-tumour heterogeneity (ITH) causes diagnostic challenges and increases the risk for disease recurrence. Quantification of ITH is challenging and has not been demonstrated in large studies. It has previously been shown that deep learn...