Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

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Leveraging immuno-fluorescence data to reduce pathologist annotation requirements in lung tumor segmentation using deep learning.

The main bottleneck in training a robust tumor segmentation algorithm for non-small cell lung cancer...

Use machine learning to predict pulmonary metastasis of esophageal cancer: a population-based study.

BACKGROUND: This study aims to establish a predictive model for assessing the risk of esophageal can...

Multitask machine learning-based tumor-associated collagen signatures predict peritoneal recurrence and disease-free survival in gastric cancer.

BACKGROUND: Accurate prediction of peritoneal recurrence for gastric cancer (GC) is crucial in clini...

Convolutional Neural Networks for Segmentation of Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).

The purpose of this study was to evaluate the impact of probability map threshold on pleural mesothe...

Upconversion and NIR-II luminescent rare earth nanoparticles combined with machine learning for cancer theranostics.

How to develop contrast agents for cancer theranostics is a meaningful and challenging endeavor, and...

Multimodal radiomics-based methods using deep learning for prediction of brain metastasis in non-small cell lung cancer withF-FDG PET/CT images.

. Approximately 57% of non-small cell lung cancer (NSCLC) patients face a 20% risk of brain metastas...

Diagnostic Value of Magnetic Resonance Imaging Radiomics and Machine-learning in Grading Soft Tissue Sarcoma: A Mini-review on the Current State.

Soft tissue sarcomas (STS) are a heterogeneous group of rare malignant tumors. Tumor grade might be ...

Applying deep learning-based ensemble model to [F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases.

OBJECTIVES: To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[F]flu...

The transformative potential of AI-driven CRISPR-Cas9 genome editing to enhance CAR T-cell therapy.

This narrative review examines the promising potential of integrating artificial intelligence (AI) w...

Severe degranulation of mesenteric mast cells in an experimental rat mammary tumor model.

BACKGROUND/AIM: Breast cancers are one of the most common cancers in women and are responsible for m...

Implementing machine learning to predict survival outcomes in patients with resected pulmonary large cell neuroendocrine carcinoma.

BACKGROUND: The post-surgical prognosis for Pulmonary Large Cell Neuroendocrine Carcinoma (PLCNEC) p...

A Multi-Scale Liver Tumor Segmentation Method Based on Residual and Hybrid Attention Enhanced Network with Contextual Integration.

Liver cancer is one of the malignancies with high mortality rates worldwide, and its timely detectio...

Clinical performance of deep learning-enhanced ultrafast whole-body scintigraphy in patients with suspected malignancy.

BACKGROUND: To evaluate the clinical performance of two deep learning methods, one utilizing real cl...

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