AIMC Topic: Antineoplastic Agents

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Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.

Scientific reports
Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomar...

Robotic compounding versus manual compounding of chemotherapy: Comparing dosing accuracy and precision.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
BACKGROUND: Cytostatic drugs are increasingly being prepared with a cytostatic robot, though it is not known whether the dose of the final product is more accurate after automated or manual preparation. This study is the first to compare accuracy and...

Machine learning for predicting pathological complete response in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy.

Scientific reports
For patients with locally advanced rectal cancer (LARC), achieving a pathological complete response (pCR) after neoadjuvant chemoradiotherapy (CRT) provides them with the optimal prognosis. However, no reliable prediction model is presently available...

Strategies for Testing Intervention Matching Schemes in Cancer.

Clinical pharmacology and therapeutics
Personalized medicine, or the tailoring of health interventions to an individual's nuanced and often unique genetic, biochemical, physiological, behavioral, and/or exposure profile, is seen by many as a biological necessity given the great heterogene...

Concise Polygenic Models for Cancer-Specific Identification of Drug-Sensitive Tumors from Their Multi-Omics Profiles.

Biomolecules
In silico models to predict which tumors will respond to a given drug are necessary for Precision Oncology. However, predictive models are only available for a handful of cases (each case being a given drug acting on tumors of a specific cancer type)...

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

Pharmacological research
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...

A comparative analysis of saponin-enriched fraction from (Moench) Garcke, (Gaertn) and (Santapau and Fernandes): an hemolytic and cytotoxicity evaluation.

Animal biotechnology
To explore the newer saponin resources, toxicity of saponin-enriched fraction (SEF) extracted from (SV) was evaluated for first time and compared with toxicity of SEF extracted from (SM) and (CV). All extracted SEF from diverse resources were cha...

Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images.

International journal of computer assisted radiology and surgery
PURPOSE: Neoadjuvant chemotherapy (NAC) aims to minimize the tumor size before surgery. Predicting response to NAC could reduce toxicity and delays to effective intervention. Computational analysis of dynamic contrast-enhanced magnetic resonance imag...