Chemotherapy

Short-term outcomes of robot-assisted versus video-assisted thoracoscopic surgery for non-small cell lung cancer patients with neoadjuvant immunochemotherapy: a single-center retrospective study.

BACKGROUND: Neoadjuvant immunochemotherapy has been increasingly applied to treat non-small cell lung cancer (NSCLC). However, the comparison between robotic-assisted thoracoscopic surgery (RATS) and video-assisted thoracoscopic surgery (VATS) in the feasibility and oncological efficacy following neoadjuvant immunochemotherapy is scarce. This study aims to assess the superiorities of RATS over (VA...

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.

BACKGROUND: Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) has demonstrated a strong correlation to improved survival in breast cancer (BC) patients. However, pCR rates to NAC are less than 30%, depending on the BC subtype. Early prediction of NAC response would facilitate therapeutic modifications for individual patients, potentially improving overall treatment outcomes an...

Deep learning radio-clinical signatures for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients.

BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of l...

Intelligent solution predictive networks for non-linear tumor-immune delayed model.

In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the imm...

Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The pu...

Predicting Neoadjuvant Chemotherapy Response and High-Grade Serous Ovarian Cancer From CT Images in Ovarian Cancer with Multitask Deep Learning: A Multicenter Study.

RATIONALE AND OBJECTIVES: Accurate prediction neoadjuvant chemotherapy (NACT) response in ovarian cancer (OC) is essential for personalized medicine. ...

Phytochemical Screening, HPTLC Fingerprinting and Evaluation of In Vitro Cytotoxic Activity of Stem Bark Extracts of O (L.) Vent. Against Human Cervical Cancer Cells.

a well-known traditional medicinal plant which is used to alleviate various kinds of diseases in Asia. The study aimed to identify bioactive compound...

Game-based learning as training to use a chemotherapy preparation robot.

INTRODUCTION: In 2015, our university hospital pharmacy acquired the PharmaHelp robot system to automate part of its chemotherapy production. Complex ...

Robot Assisted Laparoscopy Combined with Thoracoscopy in the Treatment of Hepatocellular Carcinoma with Inferior Vena Cava Tumor Thrombus.

BACKGROUND: Facing the 0.7-22% incidence rate of hepatocellular carcinoma (HCC) with inferior vena cava tumor thrombus (IVCTT), there are usually no o...

Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data.

Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic substances in environmental samples. However, new ...

Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.

RATIONALE AND OBJECTIVES: To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elas...

Emerging uses of artificial intelligence in breast and axillary ultrasound.

Breast ultrasound is a valuable adjunctive tool to mammography in detecting breast cancer, especially in women with dense breasts. Ultrasound also pla...

[Robotic production of injectable anticancer drugs in hospital pharmacies].

INTRODUCTION: Following the 2005 decree on securing the medicine supply chain, the production of "chemotherapies", anticancer drugs (cytotoxic, cytost...

Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial.

BACKGROUND: Pretreatment identification of pathological extranodal extension (ENE) would guide therapy de-escalation strategies for in human papilloma...

Deep learning of endoscopic features for the assessment of neoadjuvant therapy response in locally advanced rectal cancer.

BACKGROUND: For locally advanced rectal cancer (LARC), accurate response evaluation is necessary to select complete responders after neoadjuvant thera...

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations.

Inhibition of pathological angiogenesis has become one of the first FDA approved targeted therapies widely tested in anti-cancer treatment, i.e. VEGF-...

Trustworthy Deep Neural Network for Inferring Anticancer Synergistic Combinations.

The lack of a gold standard synergy quantification method for chemotherapeutic drug combinations warrants the consideration of different synergy metri...

Review of Robot-Assisted HIFU Therapy.

This paper provides an overview of current robot-assisted high-intensity focused ultrasound (HIFU) systems for image-guided therapies. HIFU is a minim...

A Deep-Learning-Computed Cancer Score for the Identification of Human Hepatocellular Carcinoma Area Based on a Six-Colour Multiplex Immunofluorescence Panel.

Liver cancer is one of the most frequently diagnosed and fatal cancers worldwide, with hepatocellular carcinoma (HCC) being the most common primary li...

A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status.

Oncology treatments require continuous individual adjustment based on the measurement of multiple clinical parameters. Prediction tools exploiting the...