Article
Multidisciplinary Sciences
Noor Sajid, Emma Holmes, Thomas M. Hope, Zafeirios Fountas, Cathy J. Price, Karl J. Friston
Summary: Functional recovery after brain damage varies depending on factors such as lesion site and extent. Recovery can occur by engaging residual components or utilizing intact neural structures, with different types of lesions having different effects.
SCIENTIFIC REPORTS
(2021)
Article
Biotechnology & Applied Microbiology
Ruifeng Bai, Mingwei Zhou
Summary: In this paper, we propose a skin lesion segmentation network based on HarDNet (SL-HarDNet). By introducing cascaded fusion module (CFM), spatial channel attention module (SCAM) and feature aggregation module (FAM), automatic segmentation of skin lesions is achieved. Experimental results show that SL-HarDNet outperforms other methods and achieves state-of-the-art segmentation performance.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2023)
Editorial Material
Dermatology
Sanaa Butt, Alan Evans, Cathy Green, Andrew Affleck
Summary: This case presents a 23-year-old man with a 1-year history of a lesion on the right cheek. The tumor can mimic other benign lesions, such as pilomatrixoma or benign cysts, as it lacks distinctive clinical or dermoscopic features. However, it is concerning as malignant transformation can occur, making surgery necessary for both diagnosis and treatment.
CLINICAL AND EXPERIMENTAL DERMATOLOGY
(2022)
Article
Medicine, General & Internal
Peter Marosan-Vilimszky, Klara Szalai, Andras Horvath, Domonkos Csabai, Krisztian Fuzesi, Gergely Csany, Miklos Gyongy
Summary: The study introduces a framework for skin cancer classification using fully automatic and semi-automatic segmentation methods, trained on ultrasound recordings, with promising results. It is the first to assess the impact of fully automatic classification method, showing no significant decrease in performance.
Article
Computer Science, Artificial Intelligence
Qiangguo Jin, Hui Cui, Changming Sun, Zhaopeng Meng, Ran Su
Summary: This study introduces a cascade knowledge diffusion network to improve skin lesion classification and segmentation by utilizing knowledge learned from different tasks. The proposed network includes novel feature entanglement modules to transfer knowledge between classification and segmentation tasks effectively. Extensive evaluations with challenge datasets show superior performance without the need for ensemble approaches or external datasets.
APPLIED SOFT COMPUTING
(2021)
Article
Mathematics
Mehwish Zafar, Javeria Amin, Muhammad Sharif, Muhammad Almas Anjum, Ghulam Ali Mallah, Seifedine Kadry
Summary: In this article, a method is proposed for the segmentation and classification of skin lesions using a pre-trained model, which achieves high classification accuracy.
Article
Multidisciplinary Sciences
Shubham Innani, Prasad Dutande, Ujjwal Baid, Venu Pokuri, Spyridon Bakas, Sanjay Talbar, Bhakti Baheti, Sharath Chandra Guntuku
Summary: This paper introduces a framework called EGAN for skin lesion segmentation using computer-aided diagnosis tools. The EGAN framework generates accurate lesion masks through adversarial learning and achieves superior performance on the International Skin Imaging Collaboration Lesion Dataset. Additionally, a lightweight segmentation framework called MGAN is proposed, which achieves comparable performance to EGAN but with fewer training parameters, resulting in faster inference times for low compute resource settings.
SCIENTIFIC REPORTS
(2023)
Letter
Medicine, General & Internal
Markus Mueller, Barbara Ingold-Heppner, Hartmut Stocker, Frank L. Heppner, Carsten Dittmayer, Michael Laue
Summary: Our study provides new insights into the ultrastructural presentation of mpox infection in the colon, which differs from the presentation in the skin and has not been previously documented. We also highlight the occurrence of proctitis and severe anal pain as frequently observed symptoms of mpox, which differ from previously described symptoms. The patient in our case underwent anorectoscopy and tissue extraction from anal ulcerating lesions to exclude other differential diagnoses, including neoplasms.
Article
Computer Science, Artificial Intelligence
Zahra Mirikharaji, Kumar Abhishek, Alceu Bissoto, Catarina Barata, Sandra Avila, Eduardo Valle, M. Emre Celebi, Ghassan Hamarneh
Summary: Skin cancer is a major health problem that can be alleviated through computer-aided diagnosis. However, skin lesion segmentation is challenging due to various factors. This survey examines deep learning-based methods for skin lesion segmentation and analyzes their input data, model design, and evaluation aspects.
MEDICAL IMAGE ANALYSIS
(2023)
Review
Environmental Sciences
Shahanaj Parvin, Md. Hashmi Sakib, Md. Latiful Islam, Christopher L. Brown, Md. Saiful Islam, Yahia Mahmud
Summary: The Sundarbans, a unique natural shield in Bangladesh, plays a critical role in protecting coastal aquaculture. However, the impacts of climate change pose a threat to this sector, highlighting the need for implementing safe farming practices to safeguard the Sundarbans.
MARINE POLLUTION BULLETIN
(2023)
Article
Agriculture, Dairy & Animal Science
Matthew Barden, Alkiviadis Anagnostopoulos, Bethany E. Griffiths, Bingjie Li, Cherry Bedford, Chris Watson, Androniki Psifidi, Georgios Banos, Georgios Oikonomou
Summary: This study aimed to estimate the genetic parameters of recovery from sole lesions in dairy cows and evaluate its genetic correlation with overall susceptibility. The findings showed that recovery from sole lesions is heritable and negatively correlated with susceptibility. If confirmed in further research, selective breeding could be used to reduce the frequency of chronically lame cows.
JOURNAL OF DAIRY SCIENCE
(2023)
Review
Medicine, General & Internal
Taye Girma Debelee
Summary: This survey paper reviews the latest methods for skin lesion classification, segmentation, and detection, highlighting the importance of skin lesion analysis in healthcare and the challenges it poses. It covers various techniques used in the selected study papers and discusses the difficulties and approaches in skin lesion segmentation and detection. The survey also provides an overview of notable datasets, benchmark challenges, and evaluation metrics in the field, and concludes with a summary of major trends and potential future directions in skin lesion analysis.
Article
Green & Sustainable Science & Technology
Hamidul Huq, Md. Mizanur Rahman, M. Anwar Hossen
Summary: This study reveals the adaptive strategies of women in response to the vulnerabilities engendered by climate change. It highlights the substantial contributions of women in adapting to climate change impacts and emphasizes the need to recognize and replicate their approaches.
Article
Computer Science, Artificial Intelligence
Catarina Barata, M. Emre Celebi, Jorge S. Marques
Summary: This study aims to address the lack of explainability in deep learning methods in medical diagnostic systems, improving the safety of skin cancer diagnostic systems. By combining medical knowledge and recent advances, a diagnostic system with competitive results was successfully developed.
PATTERN RECOGNITION
(2021)
Article
Medicine, General & Internal
Rabbia Mahum, Suliman Aladhadh
Summary: In this study, a novel and robust skin cancer detection model based on features fusion was proposed. The proposed model achieved high accuracy and performance in the classification of skin cancer. Compared to existing techniques, this method demonstrated better detection capability.
Article
Environmental Sciences
Yue Qian Tan, S. K. Abdur Rashid, Wen-Chi Pan, Yu-Cheng Chen, Liya E. Yu, Wei Jie Seow
SCIENCE OF THE TOTAL ENVIRONMENT
(2020)
Article
Environmental Sciences
Chih-Da Wu, Yinq-Rong Chern, Wen-Chi Pan, Shih-Chun Candice Lung, Tsung-Chieh Yao, Hui-Ju Tsai, John D. Spengler
SCIENCE OF THE TOTAL ENVIRONMENT
(2020)
Article
Allergy
Nirmin F. Juber, Chien-Chang Lee, Wen-Chi Pan, Jason J. Liu
Summary: This study found that having pediatric asthma is associated with increased risks of hypertension, diabetes, and stomach diseases diagnosed in adulthood. The associations may vary by sex and age of asthma and other NCD diagnoses.
PEDIATRIC ALLERGY AND IMMUNOLOGY
(2021)
Letter
Allergy
Tsung-Chieh Yao, Hsin-Yi Huang, Wen-Chi Pan, Chao-Yi Wu, Shun-Yu Tsai, Chi-Yen Hung, Kun-Lin Lu, Ju Chang-Chien, Chih-Lin Tseng, Chih-Da Wu, Yu-Chen Chen, Yvonne J. Huang, Hui-Ju Tsai
Article
Environmental Sciences
Hui-Ju Tsai, Chia-Ying Li, Wen-Chi Pan, Tsung-Chieh Yao, Huey-Jen Su, Chih-Da Wu, Yinq-Rong Chern, John D. Spengler
Summary: This study found that greater exposure to surrounding greenness is associated with a lower incidence of type 2 diabetes Mellitus in Taiwan.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Multidisciplinary Sciences
Aji Kusumaning Asri, Wen-Chi Pan, Hsiao-Yun Lee, Huey-Jen Su, Chih-Da Wu, John D. Spengler
Summary: This study identified significant spatial patterns and hotspots of LRIs globally, with a consistent positive association between LRIs and PM2.5. Subgroup analysis revealed significant effects of PM2.5 on LRI for children and the elderly, except for regions comprising Eastern Mediterranean countries.
SCIENTIFIC REPORTS
(2021)
Article
Public, Environmental & Occupational Health
Wen-Chi Pan, Szu-Yu Yeh, Chih-Da Wu, Yen-Tsung Huang, Yu-Cheng Chen, Chien-Jen Chen, Hwai- Yang
Summary: The study found that exposure to exhaust from small cars and trucks is associated with increased CVD mortality, with PM2.5 playing a mediation role in the relationship between traffic and CVD mortality.
JOURNAL OF EPIDEMIOLOGY
(2021)
Article
Multidisciplinary Sciences
Chao-Yi Wu, Hsin-Yi Huang, Wen-Chi Pan, Sui-Ling Liao, Man-Chin Hua, Ming-Han Tsai, Shen-Hao Lai, Kuo-Wei Yeh, Li-Chen Chen, Jing-Long Huang, Tsung-Chieh Yao
Summary: This study revealed that nearly half of allergic diseases in Asian children in Taiwan are attributable to atopy, with a higher risk among adolescents. Sensitization to mites had the highest population attributable risks for all three allergic diseases, followed by sensitization to foods.
SCIENTIFIC REPORTS
(2021)
Article
Environmental Sciences
Sepridawati Siregar, Nora Idiawati, Wen-Chi Pan, Kuo-Pin Yu
Summary: Long-term exposure to PM2.5 is associated with a higher prevalence of cardiovascular disease in residents of Sumatera, Indonesia.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Ecology
Aji Kusumaning Asri, Hsiao-Yun Lee, Wen-Chi Pan, Hui-Ju Tsai, Hao-Ting Chang, Shih-Chun Candice Lung, Huey-Jen Su, Chia-Pin Yu, John S. Ji, Chih-Da Wu, John D. Spengler
Summary: Exposure to green spaces significantly reduced the risk of depressive disorders in Indonesia, with a 5% decrease in risk per interquartile unit increment of NDVI. Additionally, a 12.4% decrease in risk was associated with an 8.4% increase in forest and total vegetation. In highly urbanized areas, green spaces were found to decrease the risk of depressive disorders by 10%. These findings could provide valuable insights for urban planning in developing countries, emphasizing the importance of green spaces for mental health.
LANDSCAPE AND URBAN PLANNING
(2021)
Article
Environmental Sciences
Mei-Sheng Ku, Wen-Chi Pan, Yen-Tsung Huang, Wu-Shiun Hsieh, Yi-Hsiang Hsu, Pau-Chung Chen, Chen-Yu Liu
Summary: Prenatal exposure to PFAS, particularly PFOS, is associated with lower methylation levels at the MEST promoter region, providing a potential mechanism for the effects of PFAS on fetal growth.
ENVIRONMENTAL POLLUTION
(2022)
Article
Environmental Sciences
Aji Kusumaning Asri, Tsunglin Liu, Hui-Ju Tsai, Hsiao-Yun Lee, Wen-Chi Pan, Chih-Da Wu, Jiu-Yao Wang
Summary: This study investigated the association between residential greenness and air pollution with nasal microbiota among asthmatic children during the recovery phase. The results showed that short-term exposure to air pollution was negatively associated with nasal bacterial diversity, while greenness was positively associated. These findings contribute to the understanding of the role of environmental exposure in nasal microbiota and its impact on asthma development.
ENVIRONMENTAL RESEARCH
(2023)
Article
Environmental Sciences
Yueh Jia Lee, Wei Qi Loh, Trung Kien Dang, Cecilia Woon Chien Teng, Wen-Chi Pan, Chih-Da Wu, Sin Eng Chia, Wei Jie Seow
Summary: Living in green environments may increase the risk of prostate cancer. This Singapore study found that individuals with a BMI in the second quartile had higher levels of NDVI compared to those in the lowest quartile. Additionally, being widowed or separated was associated with lower levels of NDVI compared to being married. The study also found that an increase in NDVI was positively associated with prostate cancer risk.
ENVIRONMENTAL RESEARCH
(2023)
Article
Public, Environmental & Occupational Health
Tzu-Yi Lu, Chih-Da Wu, Yen-Tsung Huang, Yu-Cheng Chen, Chien-Jen Chen, Hwai- Yang, Wen-Chi Pan
Summary: This study investigated the association between metal constituents in PM2.5 and the risk of liver cancer. Long-term exposure to copper (Cu) in PM2.5 was found to be positively associated with the risk of liver cancer. The findings suggest that copper in PM2.5 may contribute to the association between PM2.5 exposure and liver cancer.
JOURNAL OF EPIDEMIOLOGY
(2023)
Article
Environmental Sciences
Tuan Hung Ngo, Wen Chi Pan, Alexander Waits
Summary: Measures to restrict international travel in Taiwan resulted in a significant reduction of aviation volume and air pollution concentrations. However, the contribution of aviation to air pollution was masked by industrial activities and ground traffic.
AEROSOL AND AIR QUALITY RESEARCH
(2022)