Oncology/Hematology

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

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CT image denoising methods for image quality improvement and radiation dose reduction.

With the ever-increasing use of computed tomography (CT), concerns about its radiation dose have bec...

Detection of circulating plasma cells in peripheral blood using deep learning-based morphological analysis.

BACKGROUND: The presence of circulating plasma cells (CPCs) is an important laboratory indicator for...

Bioinformatics and Machine Learning Methods Identified MGST1 and QPCT as Novel Biomarkers for Severe Acute Pancreatitis.

Severe acute pancreatitis (SAP) is a life-threatening gastrointestinal emergency. The study aimed to...

Identification of Co-diagnostic Genes for Heart Failure and Hepatocellular Carcinoma Through WGCNA and Machine Learning Algorithms.

This research delves into the intricate relationship between hepatocellular carcinoma (HCC) and hear...

Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning.

Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by t...

Explainable deep learning-based survival prediction for non-small cell lung cancer patients undergoing radical radiotherapy.

BACKGROUND AND PURPOSE: Survival is frequently assessed using Cox proportional hazards (CPH) regress...

Comparing robotic with laparoscopic beyond total mesorectal excision for advanced rectal cancer-a propensity-matched analysis.

AIM: Robotic surgery is increasingly being used for rectal resection, with short-term benefits such ...

Prediction on nature of cancer by fuzzy graphoidal covering number using artificial neural network.

Predicting the chances of various types of cancers for different organs in the human body is a typic...

An Overview of Advances in Rare Cancer Diagnosis and Treatment.

Cancer stands as the leading global cause of mortality, with rare cancer comprising 230 distinct sub...

High-accuracy prediction of colorectal cancer chemotherapy efficacy using machine learning applied to gene expression data.

FOLFOX and FOLFIRI chemotherapy are considered standard first-line treatment options for colorectal...

Tumor-associated microbiome features of metastatic colorectal cancer and clinical implications.

BACKGROUND: Colon microbiome composition contributes to the pathogenesis of colorectal cancer (CRC) ...

Hollow CoFe Nanozymes Integrated with Oncolytic Peptides Designed via Machine-Learning for Tumor Therapy.

Developing novel substances to synergize with nanozymes is a challenging yet indispensable task to e...

Artificial intelligence across oncology specialties: current applications and emerging tools.

Oncology is becoming increasingly personalised through advancements in precision in diagnostics and ...

Integration of multi-omics and clinical treatment data reveals bladder cancer therapeutic vulnerability gene combinations and prognostic risks.

BACKGROUND: Bladder cancer (BCa) is a common malignancy of the urinary tract. Due to the high hetero...

Histopathology image classification: highlighting the gap between manual analysis and AI automation.

The field of histopathological image analysis has evolved significantly with the advent of digital p...

Predicting cervical intraepithelial neoplasia and determining the follow-up period in high-risk human papillomavirus patients.

PURPOSE: Despite strong efforts to promote human papillomavirus (HPV) vaccine and cervical cancer sc...

Quality of information and appropriateness of Open AI outputs for prostate cancer.

Chat-GPT, a natural language processing (NLP) tool created by Open-AI, can potentially be used as a ...

Machine Learning in Modeling Disease Trajectory and Treatment Outcomes: An Emerging Enabler for Model-Informed Precision Medicine.

The increasing breadth and depth of resolution in biological and clinical data, including -omics and...

Machine learning-based CT texture analysis in the differentiation of testicular masses.

PURPOSE: To evaluate the ability of texture features for distinguishing between benign and malignant...

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