AIMC Topic: Neoplasms

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Leveraging advances in immunopathology and artificial intelligence to analyze in vitro tumor models in composition and space.

Advanced drug delivery reviews
Cancer is the leading cause of death worldwide. Unfortunately, efforts to understand this disease are confounded by the complex, heterogenous tumor microenvironment (TME). Better understanding of the TME could lead to novel diagnostic, prognostic, an...

Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality.

Molecular cancer
BACKGROUND: Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a significant effect on cell viability. This concept can be exploited to specifically target tumor cells...

Saliency-guided deep learning network for automatic tumor bed volume delineation in post-operative breast irradiation.

Physics in medicine and biology
Efficient, reliable and reproducible target volume delineation is a key step in the effective planning of breast radiotherapy. However, post-operative breast target delineation is challenging as the contrast between the tumor bed volume (TBV) and nor...

Automatic registration and precise tumour localization method for robot-assisted puncture procedure under inconsistent breath-holding conditions.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: During percutaneous puncture procedure, breath holding is subjectively controlled by patients, and it is difficult to ensure consistent tumour position between the preoperative CT scanning phase and the intraoperative puncture phase. In a...

Cancer survivorship care and general practice: A qualitative study of roles of general practice team members in Australia.

Health & social care in the community
Primary care providers, including general practice teams (GPTs), are well positioned within the community to integrate cancer survivorship care into ongoing health management. However, roles of GPT members in delivery of cancer survivorship care have...

Preface.

Biochimica et biophysica acta. Reviews on cancer

Predicting and characterizing a cancer dependency map of tumors with deep learning.

Science advances
Genome-wide loss-of-function screens have revealed genes essential for cancer cell proliferation, called cancer dependencies. It remains challenging to link cancer dependencies to the molecular compositions of cancer cells or to unscreened cell lines...

DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.

PLoS computational biology
DNA is a complex molecule carrying the instructions an organism needs to develop, live and reproduce. In 1953, Watson and Crick discovered that DNA is composed of two chains forming a double-helix. Later on, other structures of DNA were discovered an...

Clinical implementation of deep-learning based auto-contouring tools-Experience of three French radiotherapy centers.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Deep-learning (DL)-based auto-contouring solutions have recently been proposed as a convincing alternative to decrease workload of target volumes and organs-at-risk (OAR) delineation in radiotherapy planning and improve inter-observer consistency. Ho...

Interpretable deep recommender system model for prediction of kinase inhibitor efficacy across cancer cell lines.

Scientific reports
Computational models for drug sensitivity prediction have the potential to significantly improve personalized cancer medicine. Drug sensitivity assays, combined with profiling of cancer cell lines and drugs become increasingly available for training ...