4.6 Article

Kidney Cancer Diagnosis and Surgery Selection by Machine Learning from CT Scans Combined with Clinical Metadata

Related references

Note: Only part of the references are listed.
Review Transplantation

The 'other' big complication: how chronic kidney disease impacts on cancer risks and outcomes

Jennifer S. Lees et al.

Summary: Cancer risk is higher in patients with chronic kidney disease (CKD), especially those with lower estimated glomerular filtration rate (eGFR) or albuminuria. The increased risk of cancer in CKD is influenced by various factors including patient characteristics, disease factors, and treatment factors. Renal adverse events associated with chemotherapy and newer anti-cancer therapies may contribute to worse cancer outcomes in CKD patients. Acknowledging the increased cancer risk in CKD can potentially improve management.

NEPHROLOGY DIALYSIS TRANSPLANTATION (2023)

Article Computer Science, Artificial Intelligence

Identify glomeruli in human kidney tissue images using a deep learning approach

Shubham Shubham et al.

Summary: Healthcare is the most important need in today's era, and the advancement of technology has greatly contributed to the success in the healthcare sector. Deep learning has played a crucial role in the diagnosis and treatment of diseases, such as the identification of glomeruli in the human kidney tissue.

SOFT COMPUTING (2023)

Article Radiology, Nuclear Medicine & Medical Imaging

MRI texture-based machine learning models for the evaluation of renal function on different segmentations: a proof-of-concept study

Xiaokai Mo et al.

Summary: A machine learning model based on MRI texture features can noninvasively assess renal function, providing a monitoring method for diabetic patients.

INSIGHTS INTO IMAGING (2023)

Article Social Work

COVID-19 vaccine willingness and hesitancy among residents in Qatar: a quantitative analysis based on machine learning

Muhammad Hafizh et al.

Summary: This study investigated the general outlook of Qatari residents towards the COVID-19 vaccine and their hesitations, as well as the role of the Ehteraz application in promoting vaccination. Through questionnaire surveys and data analysis, it was found that respondent characteristics can predict vaccination attitudes.

JOURNAL OF HUMAN BEHAVIOR IN THE SOCIAL ENVIRONMENT (2022)

Article Radiology, Nuclear Medicine & Medical Imaging

A deep learning system for automated kidney stone detection and volumetric segmentation on noncontrast CT scans

Daniel C. Elton et al.

Summary: This study developed a deep learning-based system for accurate detection and quantification of kidney stones, showing higher performance than previous methods and validation on a large external dataset.

MEDICAL PHYSICS (2022)

Article Computer Science, Interdisciplinary Applications

3D multi-scale residual fully convolutional neural network for segmentation of extremely large-sized kidney tumor

Ehwa Yang et al.

Summary: This study proposes a novel deep neural network, 3D Multi-Scale Residual Fully Convolutional Neural Network (3D-MS-RFCNN), to improve the segmentation of extremely large-sized kidney tumors. The network utilizes a multi-scale approach and ensemble learning strategy to capture global contextual features and achieve improved segmentation performance.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2022)

Article Computer Science, Interdisciplinary Applications

A deep learning-based precision and automatic kidney segmentation system using efficient feature pyramid networks in computed tomography images

Chiu-Han Hsiao et al.

Summary: This paper proposes an encoder-decoder architecture for kidney segmentation and implements a hyperparameter optimization process. The model achieves the best performance with a Dice score of 0.969 on the 2019 Kidney and Kidney Tumor Segmentation Challenge dataset. The proposed model is tested with different voxel spacing, anatomical planes, and kidney and tumor volumes, and case studies are conducted to analyze segmentation outliers. The developed model is evaluated using five-fold cross-validation and the 3D-IRCAD-01 dataset, demonstrating its effectiveness in image analysis and interpretation.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2022)

Article Computer Science, Artificial Intelligence

Kidney tumor segmentation from computed tomography images using DeepLabv3+2.5D model

Luana Batista da Cruz et al.

Summary: The study introduces a 2.5D network for assisting doctors in diagnosing kidney tumors in CT images, balancing memory consumption and model complexity, and providing results comparable to high-performance 3D neural networks.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Computer Science, Artificial Intelligence

Dynamic graph convolutional autoencoder with node-attribute-wise attention for kidney and tumor segmentation from CT volumes

Ping Xuan et al.

Summary: This study proposes a novel dynamic graph convolution autoencoder with node-attribute-wise attention for relation inference and reasoning, applied in kidney and tumor segmentation. The experimental results demonstrate the effectiveness of this approach, particularly in dealing with objects with weak boundaries, irregular shapes, and various sizes.

KNOWLEDGE-BASED SYSTEMS (2022)

Review Urology & Nephrology

Epidemiology of chronic kidney disease: an update 2022

Csaba P. Kovesdy

Summary: Chronic kidney disease affects over 800 million individuals worldwide, especially prevalent in older individuals, women, racial minorities, and people with diabetes and hypertension. It has become a major cause of mortality globally, particularly in low- and middle-income countries.

KIDNEY INTERNATIONAL SUPPLEMENTS (2022)

Review Cell Biology

Chronic Kidney Disease and Cancer: Inter-Relationships and Mechanisms

Mengsi Hu et al.

Summary: Chronic kidney disease (CKD) and cancer have a complex relationship, which may be associated with chronic inflammation, accumulation of carcinogenic compounds, and impaired DNA repair. Understanding this field can be helpful for both nephrologists and oncologists in clinical practice.

FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY (2022)

Article Medicine, General & Internal

QUCoughScope: An Intelligent Application to Detect COVID-19 Patients Using Cough and Breath Sounds

Tawsifur Rahman et al.

Summary: Since the outbreak of the COVID-19 pandemic, mass testing has become essential to reduce the spread of the virus. This paper introduces a novel machine learning approach that allows for the detection of COVID-19 patients (both symptomatic and asymptomatic) from the convenience of their homes, aiming to relieve the burden on healthcare systems and prevent unintentional virus transmission. By collecting cough and breath sound samples and applying a deep learning-based model, the system can accurately classify COVID-19 patients and healthy individuals, providing a pre-screening method to prioritize patients for further testing.

DIAGNOSTICS (2022)

Article Computer Science, Artificial Intelligence

BKC-Net: Bi-Knowledge Contrastive Learning for renal tumor diagnosis on 3D CT images

Jindi Kong et al.

Summary: In this paper, a novel diagnosis framework for renal tumors, named Bi-knowledge Contrastive Network (BKC-Net), is proposed. The framework utilizes focus-perceive learning and bi-knowledge contrastive learning to improve the model's performance. Experimental results demonstrate that the BKC-Net achieves the best performance in renal tumor diagnosis. The framework shows great potential for clinical use.

KNOWLEDGE-BASED SYSTEMS (2022)

Article Imaging Science & Photographic Technology

Kidney Tumor Semantic Segmentation Using Deep Learning: A Survey of State-of-the-Art

Abubaker Abdelrahman et al.

Summary: Deep learning models play a crucial role in kidney tumor segmentation, assisting clinicians in accurately identifying and segmenting tumors, and improving the efficacy of tumor treatment.

JOURNAL OF IMAGING (2022)

Article Urology & Nephrology

Distinguishing Benign Renal Tumors with an Oncocytic Gene Expression (ONEX) Classifier

Patrick D. McGillivray et al.

Summary: Renal oncocytoma is a benign form of kidney cancer that may not require surgical removal. A classification tool based on the RNA levels of nine genes was developed to reliably distinguish renal oncocytoma from other forms of kidney cancer, potentially reducing unnecessary surgeries.

EUROPEAN UROLOGY (2021)

Article Surgery

Case Report: Optimizing Pre- and Intraoperative Planning With Hyperaccuracy Three-Dimensional Virtual Models for a Challenging Case of Robotic Partial Nephrectomy for Two Complex Renal Masses in a Horseshoe Kidney

Riccardo Campi et al.

Summary: This case report describes a patient with a Horseshoe kidney who underwent robot-assisted partial nephrectomy for two highly complex renal tumors, utilizing hyperaccuracy three-dimensional virtual models for precise preoperative and intraoperative planning. Different clamping strategies were employed for the resection of the two tumors, resulting in no complications and no evidence of recurrence at a 7-month follow-up.

FRONTIERS IN SURGERY (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Automated segmentation of kidney and renal mass and automated detection of renal mass in CT urography using 3D U-Net-based deep convolutional neural network

Zhiyong Lin et al.

Summary: The study developed a 3D U-Net-based deep learning model for automated segmentation of kidney and renal mass, and detection of renal mass in CTU. The model showed high accuracy in segmentation of kidney and renal tumor, with average DSC of 0.973 and 0.844, respectively, and performed well in detecting renal tumor and cyst. The results suggest that the proposed model has promising potential for clinical applications in the segmentation and detection of kidney abnormalities.

EUROPEAN RADIOLOGY (2021)

Article Biology

COVID-19 infection localization and severity grading from chest X-ray images

Anas M. Tahir et al.

Summary: The study proposed a systematic and unified approach for lung segmentation and COVID-19 localization with infection quantification from CXR images. The largest benchmark dataset was constructed with 33,920 CXR images, including 11,956 COVID-19 samples, where ground-truth lung segmentation masks were annotated on CXRs by a human-machine collaborative approach. The developed network achieved superior performance for lung region segmentation and reliable localization of COVID-19 infections, with outstanding COVID-19 detection performance above 99% sensitivity and specificity values.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Computer Science, Artificial Intelligence

Recent advances in medical image processing for the evaluation of chronic kidney disease

Israa Alnazer et al.

Summary: The paper discusses the use of advanced imaging techniques and artificial intelligence in the assessment of renal function and structure in Chronic Kidney Disease, including methods like texture analysis and machine learning, as well as exploring the novel approach of deep learning in renal function diagnosis.

MEDICAL IMAGE ANALYSIS (2021)

Article Computer Science, Artificial Intelligence

The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge

Nicholas Heller et al.

Summary: The anatomic and geometric characteristics of kidney tumors have significant impact on surgical and oncologic outcomes. Deep learning methods have shown promising results in automatic 3D segmentations, but there is still debate on the best approach. The KiTS19 challenge provided a platform for researchers worldwide to develop automated systems for kidney and tumor segmentation using a large dataset of CT images.

MEDICAL IMAGE ANALYSIS (2021)

Article Medicine, General & Internal

Detection and Severity Classification of COVID-19 in CT Images Using Deep Learning

Yazan Qiblawey et al.

Summary: The study proposed a cascaded system to detect and quantify COVID-19 infections from CT images, achieving high sensitivity and specificity, precise localization of infections, and the ability to discriminate between different severity levels of infection. The system showed excellent performance in experiments and could accurately localize infections of various shapes and sizes, even in small infection regions rarely considered in recent studies.

DIAGNOSTICS (2021)

Article Computer Science, Interdisciplinary Applications

Cascaded Regression Neural Nets for Kidney Localization and Segmentation-free Volume Estimation

Mohammad Arafat Hussain et al.

Summary: An integrated deep learning approach for kidney localization and segmentation-free renal volume estimation is proposed in this study. The method skips the segmentation step and achieves good performance in kidney boundary wall localization error and mean volume estimation error.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2021)

Article Oncology

Deep learning for end-to-end kidney cancer diagnosis on multi-phase abdominal computed tomography

Kwang-Hyun Uhm et al.

Summary: This study proposed an end-to-end deep learning model for the differential diagnosis of five major histologic subtypes of renal tumors on multi-phase CT, achieving good diagnostic performance that even outperformed radiologists, which can help improve the accuracy of diagnosing renal tumors.

NPJ PRECISION ONCOLOGY (2021)

Article Urology & Nephrology

Renal Cell Cancer and Chronic Kidney Disease

Danielle L. Saly et al.

Summary: The association between CKD and RCC is bidirectional and multifactorial, with risk factors such as hypertension, diabetes, obesity, and smoking increasing the likelihood of both diseases. Medical therapies can also lead to acute kidney injury and CKD, necessitating clinician awareness of these complex interactions.

ADVANCES IN CHRONIC KIDNEY DISEASE (2021)

Article Urology & Nephrology

Transperitoneal vs. retroperitoneal robotic partial nephrectomy: a matched-paired analysis

Harsha R. Mittakanti et al.

WORLD JOURNAL OF UROLOGY (2020)

Article Computer Science, Artificial Intelligence

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

Ramprasaath R. Selvaraju et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Differentiation of Small (≤ 4 cm) Renal Masses on Multiphase Contrast-Enhanced CT by Deep Learning

Takashi Tanaka et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2020)

Article Pediatrics

Using Deep Learning Algorithms to Grade Hydronephrosis Severity: Toward a Clinical Adjunct

Lauren C. Smail et al.

FRONTIERS IN PEDIATRICS (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning

Mostafa Nazari et al.

RADIOLOGIA MEDICA (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Deep Learning Based on MRI for Differentiation of Low- and High-Grade in Low-Stage Renal Cell Carcinoma

Yijun Zhao et al.

JOURNAL OF MAGNETIC RESONANCE IMAGING (2020)

Article Biology

Kidney segmentation from computed tomography images using deep neural network

Luana Batista da Cruz et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Classification of renal tumour using convolutional neural networks to detect oncocytoma

Mikkel Pedersen et al.

EUROPEAN JOURNAL OF RADIOLOGY (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

CT-based machine learning model to predict the Fuhrman nuclear grade of clear cell renal cell carcinoma

Fan Lin et al.

ABDOMINAL RADIOLOGY (2019)

Article Computer Science, Interdisciplinary Applications

Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT

Yutong Xie et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

The Classification of Renal Cancer in 3-Phase CT Images Using a Deep Learning Method

Seokmin Han et al.

JOURNAL OF DIGITAL IMAGING (2019)

Article Computer Science, Artificial Intelligence

Crossbar-Net: A Novel Convolutional Neural Network for Kidney Tumor Segmentation in CT Images

Qian Yu et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2019)

Article Chemistry, Multidisciplinary

TF-YOLO: An Improved Incremental Network for Real-Time Object Detection

Wangpeng He et al.

APPLIED SCIENCES-BASEL (2019)

Article Respiratory System

Consequences of chronic kidney disease in chronic obstructive pulmonary disease

Franziska C. Trudzinski et al.

RESPIRATORY RESEARCH (2019)

Article Computer Science, Interdisciplinary Applications

Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks

Lequan Yu et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2017)

Review Medicine, General & Internal

Chronic kidney disease

Angela C. Webster et al.

LANCET (2017)

Article Medicine, General & Internal

Renal cell carcinoma

James J. Hsieh et al.

NATURE REVIEWS DISEASE PRIMERS (2017)

Article Urology & Nephrology

The Role of PET Scanning in the Evaluation of Patients With Kidney Disease

Namrata Krishnan et al.

ADVANCES IN CHRONIC KIDNEY DISEASE (2017)

Article Computer Science, Hardware & Architecture

ImageNet Classification with Deep Convolutional Neural Networks

Alex Krizhevsky et al.

COMMUNICATIONS OF THE ACM (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Densely Connected Convolutional Networks

Gao Huang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Review Urology & Nephrology

The Epidemiology of Renal Cell Carcinoma

Borje Ljungberg et al.

EUROPEAN UROLOGY (2011)

Review Urology & Nephrology

Epidemiology and risk factors for kidney cancer

Wong-Ho Chow et al.

NATURE REVIEWS UROLOGY (2010)

Article Urology & Nephrology

Alcohol consumption and the risk of end-stage renal disease among Chinese men

K. Reynolds et al.

KIDNEY INTERNATIONAL (2008)