Oncology/Hematology

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

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Survival analysis of localized prostate cancer with deep learning.

In recent years, data-driven, deep-learning-based models have shown great promise in medical risk pr...

A Deep Learning-Based Computer Aided Detection (CAD) System for Difficult-to-Detect Brain Metastases.

PURPOSE: We sought to develop a computer-aided detection (CAD) system that optimally augments human ...

Raman spectroscopy combined with deep learning for rapid detection of melanoma at the single cell level.

Melanoma is an aggressive and metastatic skin cancer caused by genetic mutations in melanocytes, and...

Staging Paro: The care of making robot(s) care.

Paro, a baby seal robot, is arguably the best-known care robot worldwide. Its clinical effects on pe...

Kidney Tumor Detection and Classification Based on Deep Learning Approaches: A New Dataset in CT Scans.

Kidney tumor (KT) is one of the diseases that have affected our society and is the seventh most comm...

Clinical target volume segmentation based on gross tumor volume using deep learning for head and neck cancer treatment.

Accurate clinical target volume (CTV) delineation is important for head and neck intensity-modulated...

Construction of VGG16 Convolution Neural Network (VGG16_CNN) Classifier with NestNet-Based Segmentation Paradigm for Brain Metastasis Classification.

Brain metastases (BMs) happen often in patients with metastatic cancer (MC), requiring initial and p...

Automated classification of estrous stage in rodents using deep learning.

The rodent estrous cycle modulates a range of biological functions, from gene expression to behavior...

Deep learning diagnostics for bladder tumor identification and grade prediction using RGB method.

We evaluate the diagnostic performance of deep learning artificial intelligence (AI) for bladder can...

Input feature design and its impact on the performance of deep learning models for predicting fluence maps in intensity-modulated radiation therapy.

. Deep learning (DL) models for fluence map prediction (FMP) have great potential to reduce treatmen...

Applying interpretable machine learning workflow to evaluate exposure-response relationships for large-molecule oncology drugs.

The application of logistic regression (LR) and Cox Proportional Hazard (CoxPH) models are well-esta...

SurvivalCNN: A deep learning-based method for gastric cancer survival prediction using radiological imaging data and clinicopathological variables.

Radiological images have shown promising effects in patient prognostication. Deep learning provides ...

Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications.

Artificial intelligence (AI) is increasingly being studied in musculoskeletal oncology imaging. AI h...

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocar...

Clinical applicability of deep learning-based respiratory signal prediction models for four-dimensional radiation therapy.

For accurate respiration gated radiation therapy, compensation for the beam latency of the beam cont...

CTRR-ncRNA: A Knowledgebase for Cancer Therapy Resistance and Recurrence Associated Non-coding RNAs.

Cancer therapy resistance and recurrence (CTRR) are the dominant causes of death in cancer patients....

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