Oncology/Hematology

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

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Showing 6112-6132 of 15,618 articles
Robot-assisted laparoscopic versus open partial nephrectomy for renal cell carcinoma in patients with severe chronic kidney disease.

OBJECTIVES: To compare surgical and functional outcomes between robot-assisted laparoscopic partial ...

Sampling Based Tumor Recognition in Whole-Slide Histology Image With Deep Learning Approaches.

Histopathological identification of tumor tissue is one of the routine pathological diagnoses for pa...

Deep learning predicts resistance to neoadjuvant chemotherapy for locally advanced gastric cancer: a multicenter study.

BACKGROUND: Accurate pre-treatment prediction of neoadjuvant chemotherapy (NACT) resistance in patie...

Meta-analysis of robot-assisted versus video-assisted McKeown esophagectomy for esophageal cancer.

We aim to review the available literature on patients with esophageal cancer treated with robot-assi...

Simultaneous regression and classification for drug sensitivity prediction using an advanced random forest method.

Machine learning methods trained on cancer cell line panels are intensively studied for the predicti...

Automated Lung Cancer Segmentation Using a PET and CT Dual-Modality Deep Learning Neural Network.

PURPOSE: To develop an automated lung tumor segmentation method for radiation therapy planning based...

Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra.

The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distingui...

BrainNet: Optimal Deep Learning Feature Fusion for Brain Tumor Classification.

Early detection of brain tumors can save precious human life. This work presents a fully automated d...

A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity.

The complex feature characteristics and low contrast of cancer lesions, a high degree of inter-class...

A systematic review on machine learning and deep learning techniques in cancer survival prediction.

Cancer is a disease which is characterised by the unusual and uncontrollable growth of body cells. T...

Characterizing Metastable States with the Help of Machine Learning.

Present-day atomistic simulations generate long trajectories of ever more complex systems. Analyzing...

Application of the sliding window method and Mask-RCNN method to nuclear recognition in oral cytology.

BACKGROUND: We aimed to develop an artificial intelligence (AI)-assisted oral cytology method, simil...

Clavien-Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer.

Although significant progress has been made with surgical methods, the incidence of complications af...

The involvement of gut microbiota in the anti-tumor effect of carnosic acid via IL-17 suppression in colorectal cancer.

Colorectal cancer (CRC) is a malignant tumor that threatens human health worldwide. Disturbance of t...

Ovarian Cancer-Self Assessment: An Innovation for Early Detection and Risk Assessment of Ovarian Cancer.

OBJECTIVE: The modality to detect ovarian cancer at an early stage is very limited. Early diagnosis ...

Development and Validation of a Deep Learning Model for Brain Tumor Diagnosis and Classification Using Magnetic Resonance Imaging.

IMPORTANCE: Deep learning may be able to use patient magnetic resonance imaging (MRI) data to aid in...

Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques.

BACKGROUND: Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) te...

Computed Tomography-Based Deep Learning Nomogram Can Accurately Predict Lymph Node Metastasis in Gastric Cancer.

BACKGROUND: Computed tomography is the most commonly used imaging modality for preoperative assessme...

Artificial intelligence predicts lymph node metastasis or risk of lymph node metastasis in T1 colorectal cancer.

BACKGROUND: The treatment strategies for colorectal cancer (CRC) must ensure a radical cure of cance...

A New Approach to Quantify and Grade Radiation Dermatitis Using Deep-Learning Segmentation in Skin Photographs.

AIMS: Objective evaluation of radiation dermatitis is important for analysing the correlation betwee...

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