Article
Multidisciplinary Sciences
Ching-Wei Wang, Yi-An Liou, Yi-Jia Lin, Cheng-Chang Chang, Pei-Hsuan Chu, Yu-Ching Lee, Chih-Hung Wang, Tai-Kuang Chao
Summary: This study presents the first fully automated cervical lesions analysis on conventional Pap smear samples and achieves high precision, recall, F-measure, and Jaccard index in detecting high-grade cervical lesions. The proposed deep learning-based system demonstrates the ability to detect HSILs or higher with high precision and sensitivity, outperforming state-of-the-art benchmark methods in both accuracy and efficiency. The method is proven to be effective in rapidly processing whole slide images for practical clinical usage, showing promising potential for improving early diagnosis and treatment of cervical cancer.
SCIENTIFIC REPORTS
(2021)
Article
Oncology
Jing-Hang Ma, Shang-Feng You, Ji-Sen Xue, Xiao-Lin Li, Yi-Yao Chen, Yan Hu, Zhen Feng
Summary: Computer-aided diagnosis system plays an important role in cervical lesion diagnosis by using auto-segmented colposcopic images to extract features, augmenting minority data, and generating preliminary diagnosis results. The system improves sensitivity while maintaining acceptable specificity and accuracy.
FRONTIERS IN ONCOLOGY
(2022)
Article
Engineering, Biomedical
Meghana Karri, Chandra Sekhara Rao Annavarapu, Saurav Mallik, Zhongming Zhao, U. Rajendra Acharya
Summary: This paper presents a highly efficient cervical screening method based on cell image analysis and proposes a new framework for accurate classification of cervical cells. The proposed method consists of three phases: segmentation, nucleus localization, and classification. Experimental results show that the proposed approach is more effective than existing techniques.
BIOCYBERNETICS AND BIOMEDICAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Madhura M. Kalbhor, Swati V. Shinde
Summary: Cervical cancer is a feared disease that primarily affects women worldwide. Early detection through low-cost Pap smear tests is crucial for complete cure. Automated recognition and classification of Pap smear cells using deep learning methods have been proven effective in accurate diagnosis and prompt care.
Article
Computer Science, Interdisciplinary Applications
Zhu Meng, Zhicheng Zhao, Bingyang Li, Fei Su, Limei Guo
Summary: This study introduces a new cervical histopathology image dataset for automated precancerous diagnosis and demonstrates the feasibility of computer aided diagnosis through extensive experiments and methods. The proposed weakly supervised ensemble algorithm shows effectiveness in improving performance.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Nursing
Kristine N. Siseho, Beauty Etinosa Omoruyi, Benjamin Okeleye, Vincent Okudoh, Hans J. Amukugo, Yapo G. Aboua
Summary: This study examines the limiting factors associated with cervical cancer Pap smear screening among participants of reproductive age in Namibia. The results reveal that participants have limited knowledge of cervical cancer and a significant portion have never undergone the screening test before. Lack of information about the screening and its associated risks, as well as unaffordable screening fees, are identified as barriers to screening. Additionally, participants complain about the long waiting period and missed announcements as obstacles to getting screened.
Article
Biotechnology & Applied Microbiology
Yifeng Dou, Wentao Meng
Summary: This paper introduces the research, prediction, and diagnosis methods of breast cancer, using the improved optimization algorithm GSP_SVM, which shows excellent performance in breast cancer diagnosis and improves the diagnostic efficiency of medical institutions.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Pharmacology & Pharmacy
H. Salehiniya, Z. Momenimovahed, L. Allahqoli, S. Momenimovahed, I Alkatout
Summary: Cervical cancer is largely preventable, but there are various barriers to screening in Asian countries, including sociodemographic factors, awareness, attitudes and beliefs. Improving the efficacy of screening programs requires educational interventions, professional cooperation, and other measures.
EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES
(2021)
Article
Public, Environmental & Occupational Health
Lior Baruch, Avital Bilitzky-Kopit, Keren Rosen, Limor Adler
Summary: This study found that in Israel, patients with physical disabilities are less likely to receive Pap smear. Other factors associated with lower odds of receiving Pap smear include older age, lower socioeconomic status, religious minorities, cardiovascular disease, type-2 diabetes mellitus, hypertension, smoking, and obesity. Patients with a history of non-gynecologic oncologic disease had higher odds of receiving Pap smear.
JOURNAL OF WOMENS HEALTH
(2022)
Review
Pharmacology & Pharmacy
L. Allahqoli, T. Dehdari, A. Rahmani, A. Fallahi, M. Gharacheh, N. Hajinasab, H. Salehiniya, I. Alkatout
Summary: This review study aimed to identify the diagnostic delay and factors related to delayed cervical cancer diagnosis worldwide. The study found a high proportion of delayed cervical cancer diagnosis and a relatively long delay in diagnosis. Factors related to delayed diagnosis involved multiple aspects, including patient, medical history, and health system. Addressing all components of diagnostic delay and modifying factors associated with these delays are urgently needed to shorten the diagnostic journey of cervical cancer patients.
EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES
(2022)
Article
Engineering, Biomedical
Ming Zhou, Lichi Zhang, Xiaping Du, Xi Ouyang, Xin Zhang, Qijia Shen, Dong Luo, Xiangshan Fan, Qian Wang
Summary: This study proposes a novel three-stage hierarchical framework for automatic cervical smear screening, aiming at robust diagnostic performance and identifying suspected "abnormal" cells.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
(2021)
Article
Engineering, Biomedical
Marco J. Del Moral-Argumedo, Carlos A. Ochoa-Zezzati, Ruben Posada-Gomez, Alberto A. Aguilar-Lasserre
Summary: This paper presents a method for multi-class cell segmentation, achieving good performance by utilizing state-of-the-art classification architectures. The approach accurately assesses cervical cell lesions and improves healthcare for patients.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Information Systems
Mohamed Ibrahim Waly, Mohamed Yacin Sikkandar, Mohamed Abdelkader Aboamer, Seifedine Kadry, Orawit Thinnukool
Summary: This study introduces an intelligent deep convolutional neural network model for cervical cancer detection and classification using biomedical pap smear images. Experimental results demonstrate that the proposed technique shows high performance in detecting and classifying cervical cells.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Computer Science, Information Systems
Hiam Alquran, Wan Azani Mustafa, Isam Abu Qasmieh, Yasmeen Mohd Yacob, Mohammed Alsalatie, Yazan Al-Issa, Ali Mohammad Alqudah
Summary: This paper presents a computer-aided diagnostic system for classifying cervical smear images with high accuracy, achieving early detection and classification of cervical cancer with seven classes. By extracting features and utilizing SVM classifier, the system successfully distinguishes abnormality levels with high accuracy.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Wilfrido Gomez-Flores, Maria Julia Gregorio-Calas, Wagner Coelho de Albuquerque Pereira
Summary: The development of breast ultrasound CAD systems requires a set of annotated images, and this publicly available BUS dataset greatly increases the number of annotated cases and includes standardized partitions for objective evaluation and comparison of CAD systems.
Article
Agronomy
Pedro Faria, Telmo Nogueira, Ana Ferreira, Cristina Carlos, Luis Rosado
Summary: This paper presents a new methodology that embeds artificial intelligence into mobile devices to establish the use of hand-held image capture of insect traps for pest detection deployed in vineyards. By combining different computer vision approaches, the researchers achieved high quality and accuracy in image capture, leading to satisfactory experimental results.
Article
Materials Science, Multidisciplinary
Pedro Brandao, Paulo T. Silva, Marco Parente, Luis Rosado
Summary: Developing a low-cost medical device involves multiple stages of prototyping, with traditional manufacturing technologies potentially increasing development costs. This study demonstrates the development of a critical component for a low-cost microscope using novel design methodology and topology optimization to achieve the most cost-effective solution. The effectiveness of additive manufacturing prototypes in cost-effective examination and tensile strength improvement is explored, highlighting the importance of design for additive manufacturing and topology optimization as effective design tools.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART L-JOURNAL OF MATERIALS-DESIGN AND APPLICATIONS
(2022)
Article
Medicine, General & Internal
Rafaela Carvalho, Ana C. Morgado, Catarina Andrade, Tudor Nedelcu, Andre Carreiro, Maria Joao M. Vasconcelos
Summary: This study improves the diagnosis process of Teledermatology by developing a deep learning approach for risk prioritization. The results show that lesion segmentation and curriculum learning methods are beneficial for improving classification, while adding patient information does not provide much benefit in most experiments.
Article
Green & Sustainable Science & Technology
Luis Rosado, Pedro Faria, Joao Goncalves, Eduardo Silva, Ana Vasconcelos, Cristiana Braga, Joao Oliveira, Rafael Gomes, Telmo Barbosa, David Ribeiro, Telmo Nogueira, Ana Ferreira, Cristina Carlos
Summary: Due to climate change, pests pose an increasing threat to grape quality and yields. Traditional pest monitoring methods are time-consuming and require taxonomic expertise. A novel AI-powered mobile solution, EyesOnTraps, has been developed to provide efficient pest monitoring and treatment recommendations.
Review
Chemistry, Multidisciplinary
Pedro Lopes, Eduardo Silva, Cristiana Braga, Tiago Oliveira, Luis Rosado
Summary: The lack of transparency in powerful Machine Learning systems has led to the emergence of the XAI field. Researchers focus on developing explanation techniques to better understand the system's reasoning for a particular output. This paper presents a survey of Human-centred and Computer-centred methods to evaluate XAI systems, and proposes a new taxonomy for clearer categorization of these evaluation methods.
APPLIED SCIENCES-BASEL
(2022)
Article
Agronomy
Joao Goncalves, Eduardo Silva, Pedro Faria, Telmo Nogueira, Ana Ferreira, Cristina Carlos, Luis Rosado
Summary: Global warming has already had a direct impact on viticulture, particularly in terms of unexpected pests and diseases. This paper explores the use of deep learning on mobile devices to automatically identify and quantify pest counts in grape plantations. The researchers found that the SSD ResNet50 model was the most suitable for deployment on edge devices, achieving high accuracy and inference speeds.
Article
Chemistry, Multidisciplinary
Vladyslav Mosiichuk, Ana Sampaio, Paula Viana, Tiago Oliveira, Luis Rosado
Summary: Liquid-based cytology plays a crucial role in early detection of cervical cancer. This study presents a novel approach using AI-powered mobile-based solutions to detect cervical lesions on microscopic images, achieving performance improvements and reinforcing the potential of AI in cervical cancer screening.
APPLIED SCIENCES-BASEL
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Ana C. Morgado, Tomas Souper, Ana Marques, Ines Silva, Luis Rosado
Summary: This paper presents an automated approach based on Reinforcement Learning (RL) to improve color adjustments in the ceramic industry. The proposed algorithm uses spectral data to provide the best formula for achieving the target color. The results demonstrate the potential of this approach to be integrated into an AI-powered software solution for optimizing the iterative process of color (re)creation in ceramic glazes.
PROCEEDINGS OF 2023 8TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING TECHNOLOGIES, ICMLT 2023
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Tomas Souper, Ana C. Morgado, Ana Marques, Ines Silva, Luis Rosado
Summary: This study explores the use of Deep Learning to generate color mixture predictions in ceramic glazes. By using spectral data and simulating the color mixing result digitally, a fully connected neural network model achieved the best performance. This approach shows potential for improving color mixing procedures in the ceramic industry.
PROCEEDINGS OF 2023 8TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING TECHNOLOGIES, ICMLT 2023
(2023)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Maria Joao M. Vasconcelos, Dinis Moreira, Pedro Alves, Ricardo Graca, Rafael Franco, Luis Rosado
Summary: This paper presents a new method for real-time automated image acquisition and segmentation of macroscopic skin images using a combination of feature-based machine learning algorithm and conventional computer vision techniques. The proposed methodology was developed and evaluated using mobile phone images and publicly available datasets, achieving high accuracy and effectiveness. The algorithms were successfully implemented into a mobile application and tested in a real environment with positive feedback.
BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, BIOSTEC 2021
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Carlos Pereira, Paulo T. Silva, Luis Rosado, Luis Mota, Joao Martins
Summary: This article demonstrates the importance of user-focused methodologies, particularly Design Thinking, in the development of the mu SmartScope project in the field of intelligent microscopy. The article describes the design process, techniques, and tools used to gather information and how it influenced the final solution. The use of digital means during the pandemic context ensured the true essence of the methodology was not lost. The results validated the involvement of a Human-Centred Design (HCD) methodology by addressing the identified needs and designing a product that promotes a safer and more efficient relationship with the target audience.
ADVANCES IN DESIGN AND DIGITAL COMMUNICATION II
(2022)
Article
Computer Science, Information Systems
Ana Filipa Sampaio, Luis Rosado, Maria Joao M. Vasconcelos
Summary: This study introduces a low-cost, smartphone-based microscopy device for the analysis of liquid-based cytology samples, enabling autonomous image acquisition and automated identification of cervical lesions. Different deep learning models were optimized and compared to select the most suitable network architecture, with investigation into transfer learning to improve system robustness.
Article
Computer Science, Information Systems
Francisco Nunes, Pedro Madureira, Silvia Rego, Cristiana Braga, Ruben Moutinho, Tiago Oliveira, Filipe Soares
Summary: This paper introduces EyeFundusScopeNEO, a Tele-Ophthalmology system designed to support the expansion of Diabetic Retinopathy screening programmes. Preliminary studies show the potential of the system to increase the reach of screening programmes, with clinical research field trials currently being prepared.
Proceedings Paper
Computer Science, Interdisciplinary Applications
Dinis Moreira, Pedro Alves, Francisco Veiga, Luis Rosado, Maria Joao Vasconcelos
Summary: This study presents a new methodology for real-time automated image acquisition of skin images via mobile devices. The developed algorithms achieved high accuracy in image focus assessment and segmentation, with promising results for real-time usage in medium and high performance smartphones.
HEALTHINF: PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES - VOL. 5: HEALTHINF
(2021)