Oncology/Hematology

Chemotherapy

Latest AI and machine learning research in chemotherapy for healthcare professionals.

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Multiple machine learning models combined with virtual screening and molecular docking to identify selective human ALDH1A1 inhibitors.

Aldehyde dehydrogenases (ALDHs) are the enzymes of oxidoreductase family that are responsible for th...

Dexmedetomidine and Magnesium Sulfate as Adjuvant to 0.5% Ropivacaine in Supraclavicular Brachial Plexus Block: A Comparative Evaluation.

BACKGROUND: Dexmedetomidine and magnesium sulfate (MgSO) as an adjuvant to local anesthetics and ult...

5FU encapsulated polyglycerol sebacate nanoparticles as anti-cancer drug carriers.

The majority of anti-cancer drugs fail to reach clinical trials due to their low water solubility. A...

Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.

BACKGROUND: Microsatellite instability (MSI) predetermines responses to adjuvant 5-fluorouracil and ...

Adjuvant Therapy System of COVID-19 Patient: Integrating Warning, Therapy, Post-Therapy Psychological Intervention.

The 2019 novel coronavirus(COVID-19) spreads rapidly, and the large-scale infection leads to the lac...

Overcoming the limitations of patch-based learning to detect cancer in whole slide images.

Whole slide images (WSIs) pose unique challenges when training deep learning models. They are very l...

Oncologic Equipoise Between Robotic and Open Radical Cystectomy.

Our objective was to establish the incidence of positive surgical margins, recurrence patterns, and...

Magnetic tri-bead microrobot assisted near-infrared triggered combined photothermal and chemotherapy of cancer cells.

Magnetic micro/nanorobots attracted much attention in biomedical fields because of their precise mov...

High-throughput label-free detection of DNA-to-RNA transcription inhibition using brightfield microscopy and deep neural networks.

Drug discovery is in constant evolution and major advances have led to the development of in vitro h...

Predicting treatment response from longitudinal images using multi-task deep learning.

Radiographic imaging is routinely used to evaluate treatment response in solid tumors. Current imagi...

Assessing Rectal Cancer Treatment Response Using Coregistered Endorectal Photoacoustic and US Imaging Paired with Deep Learning.

Background Conventional radiologic modalities perform poorly in the radiated rectum and are often un...

Artificial neural network model to predict post-hepatectomy early recurrence of hepatocellular carcinoma without macroscopic vascular invasion.

BACKGROUND: The accurate prediction of post-hepatectomy early recurrence (PHER) of hepatocellular ca...

Development of machine learning model algorithm for prediction of 5-year soft tissue myxoid liposarcoma survival.

BACKGROUND: Predicting survival in myxoid liposarcoma (MLS) patients is very challenging given its p...

MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer.

Neoadjuvant chemo-radiotherapy (CRT) followed by total mesorectal excision (TME) represents the stan...

Is Anti-Müllerian Hormone a Marker of Ovarian Reserve in Young Breast Cancer Patients Receiving a GnRH Analog during Chemotherapy?

INTRODUCTION: Anti-Müllerian hormone (AMH) is the most reliable biomarker of ovarian reserve; howeve...

Evaluating treatment response to neoadjuvant chemoradiotherapy in rectal cancer using various MRI-based radiomics models.

BACKGROUND: To validate and compare various MRI-based radiomics models to evaluate treatment respons...

Robotic chemotherapy compounding: A multicenter productivity approach.

INTRODUCTION: The aim of this study is to compare productivity of the KIRO Oncology compounding robo...

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