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Antineoplastic Combined Chemotherapy Protocols

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Synergistic drug combinations and machine learning for drug repurposing in chordoma.

Scientific reports
Chordoma is a devastating rare cancer that affects one in a million people. With a mean-survival of just 6 years and no approved medicines, the primary treatments are surgery and radiation. In order to speed new medicines to chordoma patients, a drug...

H-RACS: a handy tool to rank anti-cancer synergistic drugs.

Aging
Though promising, identifying synergistic combinations from a large pool of candidate drugs remains challenging for cancer treatment. Due to unclear mechanism and limited confirmed cases, only a few computational algorithms are able to predict drug s...

Identification of drug combinations on the basis of machine learning to maximize anti-aging effects.

PloS one
Aging is a multifactorial process that involves numerous genetic changes, so identifying anti-aging agents is quite challenging. Age-associated genetic factors must be better understood to search appropriately for anti-aging agents. We utilized an ag...

[A Case of Locally Advanced Rectal Cancer Treated by Robot Assisted Intersphincteric Resection after Neoadjuvant Chemotherapy].

Gan to kagaku ryoho. Cancer & chemotherapy
We present a case of locally advanced rectal cancer(LARC)treated by robot assisted intersphincteric resection(ISR)and lateral lymph node dissection(LLND)after neoadjuvant chemotherapy(NAC). The patient was a 69-year-old female with the diagnosis of a...

Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models.

Methods in molecular biology (Clifton, N.J.)
Intrinsic and acquired drug resistance is a major challenge in cancer therapy. Synergistic drug combinations could help to overcome drug resistance. However, the number of possible drug combinations is enormous, and it is infeasible to experimentally...

A Prognostic Predictive System Based on Deep Learning for Locoregionally Advanced Nasopharyngeal Carcinoma.

Journal of the National Cancer Institute
BACKGROUND: Images from magnetic resonance imaging (MRI) are crucial unstructured data for prognostic evaluation in nasopharyngeal carcinoma (NPC). We developed and validated a prognostic system based on the MRI features and clinical data of locoregi...