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Field: AI in cancer detection

PolypSegNet: A modified encoder-decoder architecture for automated polyp segmentation from colonoscopy images

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Tanvir Mahmud, Bishmoy Paul, Shaikh Anowarul Fattah

Journal: Computers in Biology and Medicine
Year: 2020
Citations: 116

Colorectal cancer has become one of the major causes of death throughout the world. Early detection of Polyp, an early symptom of colorectal cancer, can increase the survival rate to 90%. Segmentation of Polyp regions from colonoscopy images can facilitate the faster diagnosis. Due to varying sizes,...

Health SciencesMedicineOncology
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Social Group Optimization–Assisted Kapur’s Entropy and Morphological Segmentation for Automated Detection of COVID-19 Infection from Computed Tomography Images

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Nilanjan Dey, V. Rajinikanth, Simon Fong, M. Shamim Kaiser et al.

Journal: Cognitive ComputationYear: 2020Citations: 116

The coronavirus disease (COVID-19) caused by a novel coronavirus, SARS-CoV-2, has been declared a global pandemic. Due to its infection rate and severity, it has emerged as one of the major global threats of the current generation. To support the current combat against the disease, this research aim...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Multi-Stage Lung Cancer Detection and Prediction Using Multi-class SVM Classifie

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Janee Alam, Sabrina Alam, Alamgir Hossan

Journal: 2018 International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2)Year: 2018Citations: 116

Recognition and prediction of lung cancer in the earliest reference point stage can be very useful to improve the survival rate of patients. But diagnosis of cancer is one the major challenging task for radiologist. For detecting, predicting and diagnosing lung cancer, an intelligent computer-aided ...

Life SciencesNeuroscienceNeurology
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Machine learning-based diagnosis of breast cancer utilizing feature optimization technique

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Khandaker Mohammad Mohi Uddin, Nitish Biswas, Sarreha Tasmin Rikta, Samrat Kumar Dey

Journal: Computer Methods and Programs in Biomedicine UpdateYear: 2023Citations: 109

Breast cancer disease is recognized as one of the leading causes of death in women worldwide after lung cancer. Breast cancer refers to a malignant neoplasm that develops from breast cells. Developed and less developed countries both are suffering from this extensive cancer. This cancer can be recup...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Classification of COVID-19 from Chest X-ray images using Deep Convolutional Neural Networks

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Sohaib Asif, Wenhui Yi, Jin Hou, Yi Tao et al.

Journal: medRxivYear: 2020Citations: 109

Abstract The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. A vital step in the combat towards COVID-19 is a successful screening of contaminated patients, with one of the key screening approaches being radiological imaging using chest...

Health SciencesMedicineRadiology, Nuclear Medicine and Imaging
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Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP

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Md. Johir Raihan, Md. Al-Masrur Khan, Seong‐Hoon Kee, Abdullah-Al Nahid

Journal: Scientific ReportsYear: 2023Citations: 107

Chronic kidney disease (CKD) is a condition distinguished by structural and functional changes to the kidney over time. Studies show that 10% of adults worldwide are affected by some kind of CKD, resulting in 1.2 million deaths. Recently, CKD has emerged as a leading cause of mortality worldwide, ma...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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BreastNet18: A High Accuracy Fine-Tuned VGG16 Model Evaluated Using Ablation Study for Diagnosing Breast Cancer from Enhanced Mammography Images

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Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Pronab Ghosh et al.

Journal: BiologyYear: 2021Citations: 104

BACKGROUND: Identification and treatment of breast cancer at an early stage can reduce mortality. Currently, mammography is the most widely used effective imaging technique in breast cancer detection. However, an erroneous mammogram based interpretation may result in false diagnosis rate, as disting...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Detecting Neurodegenerative Disease from MRI: A Brief Review on a Deep Learning Perspective

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Manan Binth Taj Noor, Nusrat Zerin Zenia, M. Shamim Kaiser, Mufti Mahmud et al.

Journal: Lecture notes in computer scienceYear: 2019Citations: 104
Life SciencesNeuroscienceNeurology
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Empowering COVID-19 detection: Optimizing performance through fine-tuned EfficientNet deep learning architecture

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Md. Alamin Talukder, Md. Abu Layek, Mohsin Kazi, Md. Ashraf Uddin et al.

Journal: Computers in Biology and MedicineYear: 2023Citations: 103

The worldwide COVID-19 pandemic has profoundly influenced the health and everyday experiences of individuals across the planet. It is a highly contagious respiratory disease requiring early and accurate detection to curb its rapid transmission. Initial testing methods primarily revolved around ident...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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A Non-Invasive Interpretable Diagnosis of Melanoma Skin Cancer Using Deep Learning and Ensemble Stacking of Machine Learning Models

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Iftiaz A. Alfi, Md. Mahfuzur Rahman, Mohammad Shorfuzzaman, Amril Nazir

Journal: DiagnosticsYear: 2022Citations: 103

A skin lesion is a portion of skin that observes abnormal growth compared to other areas of the skin. The ISIC 2018 lesion dataset has seven classes. A miniature dataset version of it is also available with only two classes: malignant and benign. Malignant tumors are tumors that are cancerous, and b...

Health SciencesMedicineOncologyOpen Access
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COVID-DenseNet: A Deep Learning Architecture to Detect COVID-19 from Chest Radiology Images

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Laboni Sarker, Md. Mohaiminul Islam, Tanveer Hannan, Zakaria Ahmed

Journal: Preprints.orgYear: 2020Citations: 102

Coronavirus disease (COVID-19) is a pandemic infectious disease that has a severe risk of spreading rapidly. The quick identification and isolation of the affected persons is the very first step to fight against this virus. In this regard, chest radiology images have been proven to be an effective s...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Machine learning-based statistical analysis for early stage detection of cervical cancer

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Md. Mamun Ali, Kawsar Ahmed, Francis M. Bui, Bikash Kumar Paul et al.

Journal: Computers in Biology and MedicineYear: 2021Citations: 100

Cervical cancer (CC) is the most common type of cancer in women and remains a significant cause of mortality, particularly in less developed countries, although it can be effectively treated if detected at an early stage. This study aimed to find efficient machine-learning-based classifying models t...

Physical SciencesComputer ScienceArtificial Intelligence
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Detection and Classification of Skin Cancer by Using a Parallel CNN Model

Verified

Noortaz Rezaoana, Mohammad Shahadat Hossain, Karl Andersson

Journal: 2020 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)Year: 2020Citations: 98

Skin cancer is one of the most lethal of all cancers. When it is not diagnosed and handled at the beginning, it is supposed to extend to other areas of the body.It also occurs while the tissue is revealed to light from the sun, mainly due to the rapid development of skin cells. For early detection, ...

Health SciencesMedicineOncologyOpen Access
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Can artificial intelligence reduce the interval cancer rate in mammography screening?

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Kristina Lång, Solveig Hofvind, Alejandro Rodríguez‐Ruiz, Ingvar Andersson

Journal: European RadiologyYear: 2021Citations: 97

OBJECTIVES: To investigate whether artificial intelligence (AI) can reduce interval cancer in mammography screening. MATERIALS AND METHODS: Preceding screening mammograms of 429 consecutive women diagnosed with interval cancer in Southern Sweden between 2013 and 2017 were analysed with a deep learni...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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DRNet: Segmentation and localization of optic disc and Fovea from diabetic retinopathy image

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Md. Kamrul Hasan, Md. Ashraful Alam, Md. Toufick E Elahi, Shidhartho Roy et al.

Journal: Artificial Intelligence in MedicineYear: 2020Citations: 97

BACKGROUND AND OBJECTIVE In modern ophthalmology, automated Computer-aided Screening Tools (CSTs) are crucial non-intrusive diagnosis methods, where an accurate segmentation of Optic Disc (OD) and localization of OD and Fovea centers are substantial integral parts. However, designing such an automat...

Health SciencesMedicineRadiology, Nuclear Medicine and Imaging
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