Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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MAPS: pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribut...

Artificial intelligence for oral squamous cell carcinoma detection based on oral photographs: A comprehensive literature review.

INTRODUCTION: Oral squamous cell carcinoma (OSCC) presents a significant global health challenge. Th...

Deep learning for automatic organ and tumor segmentation in nanomedicine pharmacokinetics.

: Multimodal imaging provides important pharmacokinetic and dosimetry information during nanomedicin...

SERS sensing for cancer biomarker: Approaches and directions.

These days, cancer is thought to be more than just one illness, with several complex subtypes that r...

Preparation and Characterisation of Zinc Diethyldithiocarbamate-Cyclodextrin Inclusion Complexes for Potential Lung Cancer Treatment.

Zinc diethyldithiocarbamate (Zn (DDC)), a disulfiram metabolite (anti-alcoholism drug), has shown a ...

Optimizing Skin Cancer Survival Prediction with Ensemble Techniques.

The advancement in cancer research using high throughput technology and artificial intelligence (AI)...

Integrative analysis of RNA expression data unveils distinct cancer types through machine learning techniques.

Cancer is a highly complex and heterogeneous disease. Traditional methods of cancer classification b...

Ct-based subregional radiomics using hand-crafted and deep learning features for prediction of therapeutic response to anti-PD1 therapy in NSCLC.

PURPOSE: To develop and externally validate subregional radiomics for predicting therapeutic respons...

Personalized Predictive Hemodynamic Management for Gynecologic Oncologic Surgery: Feasibility of Cost-Benefit Derivatives of Digital Medical Devices.

BACKGROUND: Intraoperative hypotension is associated with increased perioperative complications, hos...

Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery.

Hepatocellular carcinoma (HCC) is among the most common cancers worldwide, and tumor recurrence foll...

AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions.

PURPOSE: Implementing artificial intelligence technologies allows for the accurate prediction of rad...

Machine learning based on SEER database to predict distant metastasis of thyroid cancer.

OBJECTIVE: Distant metastasis of thyroid cancer often indicates poor prognosis, and it is important ...

Predicting Phase 1 Lymphoma Clinical Trial Durations Using Machine Learning: An In-Depth Analysis and Broad Application Insights.

Lymphoma diagnoses in the US are substantial, with an estimated 89,380 new cases in 2023, necessitat...

Laparoscopic gastrectomy for gastric cancer: A single cancer center experience.

OBJECTIVES: Laparoscopic gastrectomy (LG) was challenging to most surgeons due to the two-dimensiona...

Hydrogel spacer injection to the meso-sigmoid to protect the sigmoid colon in cervical cancer brachytherapy: A technical report.

PURPOSE: The use of a hydrogel spacer inserted into recto-vaginal fossa is a valuable strategy to mi...

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