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720 results on '"Mohamed, Ashik"'

3. Characteristics of posterior zone I retinopathy of prematurity

Author

Padhi, Tapas R., Shah, Miloni, Sahoo, Suman, Das, Taraprasad, Bhusal, Utpal, Singh, Abinash, Bhunia, Souvik, Nayak, Sameer, Nayak, Sameera, Panchal, Bhavik, Agrawal, Komal, Samantaray, Balakrushna, Devi, Sabita, Rao, Krishna, Pradhan, Lingaraj, Mohamed, Ashik, and Jalali, Subhadra

Published
2023
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6. Retinoblastoma in Asia: Clinical Presentation and Treatment Outcomes in 2112 Patients from 33 Countries

Author

Kaliki, Swathi, Vempuluru, Vijitha S., Mohamed, Ashik, Abdulqader, Rula Ahmed, Aggarwal, Priyanka, Ahmad, Alia, Akib, Marliyanti Nur Rahmah, Al Mesfer, Saleh A., Al Ani, Mouroge Hashim, Al-Badri, Safaa A.Faraj, Angeles Alcasabas, Ana Patricia, Al-Dahmash, Saad A., Al-Haddad, Christiane, Yahya Al-Hussaini, Hamoud Hodeish, Al-Jadiry, Mazin Faisal, Al-Jumaily, Usama, Alkatan, Hind Manaa, Razzaq Mahmood Al-Mafrachi, Ali Abdul, Samad Majeed Al-Shaheen, Athar Abdul, Al-Shammary, Entissar Hadi, Amiruddin, Primawita Oktarima, Armytasari, Inggar, Astbury, Nicholas John, Atalay, Hatice Tuba, Ataseven, Eda, Atchaneeyasakul, La-ongsri, Balayeva, Ruhengiz, Bascaran, Covadonga, Begimkulova, Ainura Suranovna, Bhaduri, Anirban, Bhat, Sunil, Bhattacharyya, Arpita, Blum, Sharon, Bowman, Richard, Buaboonnam, Jassada, Burton, Matthew J., Caspi, Shani, Chaudhry, Shabana, Chawla, Bhavna, Chen, Wensi, Chuluunbat, Tsengelmaa, Dangboon, Wantanee, Das, Anirban, Das, Pranab, Das, Sima, Du, Yi, Dudeja, Gagan, Eka Sutyawan, I Wayan, Fadoo, Zehra, Faranoush, Mohammad, Foster, Allen, Frenkel, Shahar, Ghassemi, Fariba, Gomel, Nir, Gunasekera, D Sanjeeva, Gündüz, Ahmet K., Gupta, Himika, Gupta, Sanjiv, Gupta, Vineeta, Hamid, Syed Ahmer, Hamzah, Norhafizah, Hasanreisoglu, Murat, Hassan, Shadab, Haydar, Huda Awni, Hongeng, Suradej, Hussein Al-Janabi, Allawi Noor, Islamov, Ziyavuddin, Janjua, Teyyeb Azeem, Jeeva, Irfan, Ji, Xunda, Jo, Dong Hyun, Kantar, Mehmet, Kapelushnik, Noa, Kebudi, Rejin, Keomisy, Jonny, Khan, Zohora Jameela, Khaqan, Hussain Ahmed, Khetan, Vikas, Khodabande, Alireza, Kim, Jeong Hun, Kiratli, Hayyam, Koç, Irem, Kulvichit, Kittisak, Kuntorini, Mayasari Wahyu, Li, Cairui, Li, Kaijun, Limbu, Ben, Liu, ChunHsiu, Lutfi, Delfitri, Mahajan, Amita, Maitra, Puja, Makimbetov, Emil Kojoshovich, Maktabi, Azza M.Y., Manzhuova, Lyazat, Masud, Sidra, Mehrvar, Azim, Menon, Vikas, John V Mercado, Gary, Chandra Mishra, Divyansh Kailash, Mohammad, Mona Tayseer, Mudaliar, Sangeeta Sanjay, Mushtaq, Asma, Nair, Akshay Gopinathan, Natarajan, Sundaram, Nency, Yetty Movieta, Neroev, Vladimir, Nuruddin, Murtuza, Pagarra, Halimah, Palanivelu, Mahesh Shanmugam, Papyan, Ruzanna, Pe'er, Jacob, Polyakov, Vladimir, Qadir, Ali Omer, Qayyum, Seema, Qian, Jiang, Quah, BoonLong, Rahman, Ardizal, Rajkarnikar, Purnima, Ramanjulu, Rajesh, Rashid, Riffat, Rojanaporn, Duangnate, Roy, Soma Rani, Saab, Raya Hamad, Saakyan, Svetlana, Sabhan, Ahmed Hatem, Saiju, Rohit, Sayalith, Phayvanh, Sedaghat, Ahad, Seth, Rachna, Shakoor, Shawkat Ara, Sharma, Manoj Kumar, Siddiqui, Sorath Noorani, Singh, Usha, Singha, Penny, Sitorus, Rita S., Soebagjo, Hendrian D., Sultana, Sadia, Sun, Xiantao, Supriyadi, Eddy, Surukrattanaskul, Supawan, Suzuki, Shigenobu, Tan, Deborah, Tang, Jing, Tashvighi, Maryam, Teh, Kok Hoi, Tehuteru, Edi Setiawan, Thawaba, Abdullah Dahan M., Toledano, Helen, Le Trang, Doan, Tripathy, Devjyoti, Tuncer, Samuray, Unal, Emel, Ushakova, Tatiana L., Usmanov, Rustam, Verma, Nishant, Victor, Andi Arus, Vishnevskia-Dai, Victoria, Wang, Yi-Zhuo, Wangtiraumnuay, Nutsuchar, Riono, Widiarti Pandu, Wiwatwongwana, Atchareeya, Wiwatwongwana, Damrong, Wong, Emily S., Wongwai, Phanthipha, Wu, Si-qi, Xiang, Daoman, Xiao, Yishuang, Xu, Bing, Xue, Kang, Yam, Jason C., Yang, Huasheng, Yaqub, Muhammad Amer, Yarovaya, Vera A., Yarovoy, Andrey A., Ye, Huijing, Yousef, Yacoub Abdallah, Yuliawati, Putu, Zhang, Yi, Zia, Nida, Zondervan, Marcia, Fabian, Ido Didi, and Sthapit, Purnima Rajkarnikar

Published
2024
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7. VLSI Implementation of BCH Encoder with Triple DES Encryption for Baseband Transceiver

Author

Dhandapani, N., Mohamed Ashik, M. Z., Bhargav, Kalthi Reddy, Achyuth, N., Jose, Deepa, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Marriwala, Nikhil, editor, Tripathi, C.C., editor, Jain, Shruti, editor, and Kumar, Dinesh, editor

Published
2023
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8. The role of maternal age & birth order on the development of unilateral and bilateral retinoblastoma: a multicentre study

Author

Lloyd, Philippa, Westcott, Mark, Kaliki, Swathi, Ji, Xunda, Zou, Yihua, Rashid, Riffat, Sultana, Sadia, Sherief, Sadik Taju, Cassoux, Nathalie, Diaz Coronado, Rosdali Yesenia, Garcia Leon, Juan Luis, López, Arturo Manuel Zapata, Polyakov, Vladimir G., Ushakova, Tatiana L., Roy, Soma Rani, Ahmad, Alia, Harby, Lamis Al, Berry, Jesse L., Kim, Jonathan, Polski, Ashley, Astbury, Nicholas J., Bascaran, Covadonga, Blum, Sharon, Bowman, Richard, Burton, Matthew J., Foster, Allen, Gomel, Nir, Keren-Froim, Naama, Madgar, Shiran, Stacey, Andrew W., Mohamed, Ashik, Zondervan, Marcia, Sagoo, Mandeep S., Fabian, Ido Didi, and Reddy, M. Ashwin

Published
2023
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21. Bias Mitigation via Synthetic Data Generation: A Review.

Author

Shahul Hameed, Mohamed Ashik, Qureshi, Asifa Mehmood, and Kaushik, Abhishek

Subjects
ARTIFICIAL intelligence, HEALTH equity, DATA quality, FAIRNESS, FORECASTING
Abstract

Artificial intelligence (AI) is widely used in healthcare applications to perform various tasks. Although these models have great potential to improve the healthcare system, they have also raised significant ethical concerns, including biases that increase the risk of health disparities in medical applications. The under-representation of a specific group can lead to bias in the datasets that are being replicated in the AI models. These disadvantaged groups are disproportionately affected by bias because they may have less accurate algorithmic forecasts or underestimate the need for treatment. One solution to eliminate bias is to use synthetic samples or artificially generated data to balance datasets. Therefore, the purpose of this study is to review and evaluate how synthetic data can be generated and used to mitigate biases, specifically focusing on the medical domain. We explored high-quality peer-reviewed articles that were focused on synthetic data generation to eliminate bias. These studies were selected based on our defined inclusion criteria and exclusion criteria and the quality of the content. The findings reveal that generated synthetic data can help improve accuracy, precision, and fairness. However, the effectiveness of synthetic data is closely dependent on the quality of the data generation process and the initial datasets used. The study also highlights the need for continuous improvement in synthetic data generation techniques and the importance of evaluation metrics for fairness in AI models. [ABSTRACT FROM AUTHOR]

Published
2024
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38. Lost-to-follow-up: A study on corneal transplantation from Eastern India

Author

Dutta, Anirban, Panigrahi, Swayam, Mohamed, Ashik, and Das, Sujata

Subjects
Medical care, Cost of -- Analysis, Visual acuity -- Analysis, Medical consultation -- Methods, Cornea -- Transplantation, Health
Abstract

Byline: Anirban. Dutta, Swayam. Panigrahi, Ashik. Mohamed, Sujata. Das Purpose: This study aims to analyze the pattern of follow-ups and the reasons for follow-up loss in keratoplasty cases in a [...]

Published
2023

39. Scleral thickness in normal Indian eyes measured using spectral domain anterior segment optical coherence tomography

Author

Kommula, Hasna, Murthy, Somasheila, Loomba, Abhinav, Mohamed, Ashik, and Ranjan, Rashmi

Subjects
Corneal diseases -- Diagnosis -- Care and treatment, Visual acuity -- Analysis, Patient compliance -- Methods, Coherence (Optics) -- Analysis, Optical tomography -- Analysis, Health
Abstract

Byline: Hasna. Kommula, Somasheila. Murthy, Abhinav. Loomba, Ashik. Mohamed, Rashmi. Ranjan Purpose: To establish normative data on anterior scleral thickness using the spectral domain anterior segment optical coherence tomography (AS-OCT). [...]

Published
2023

47. Clinical differentiation of keratitis due to fungus and Pythium: A photographic survey

Author

D'Cruz, Rakhi, Mohamed, Ashik, and Das, Sujata

Subjects
Diagnosis, Differential -- Surveys, Parasitic diseases -- Diagnosis -- Surveys, Physicians -- Surveys, Keratitis -- Diagnosis -- Surveys, Health
Abstract

Byline: Rakhi. D'cruz, Ashik. Mohamed, Sujata. Das Purpose: To evaluate the knowledge and skills of clinicians in differentiating cases of Pythium from fungal keratitis based on their clinical appearance. Methods: [...]

Published
2023

48. Factors affecting the epithelial integrity of human donor corneas

Author

Kaur, Amanjot, Mohamed, Ashik, Priyadarshini, Smruti, Mohanty, Amrita, Sahu, Srikant, and Das, Sujata

Subjects
Medical research, Medicine, Experimental, Cornea -- Storage, Medical care -- Quality management, Donation of organs, tissues, etc. -- Evaluation, Health
Abstract

Byline: Amanjot. Kaur, Ashik. Mohamed, Smruti. Priyadarshini, Amrita. Mohanty, Srikant. Sahu, Sujata. Das Purpose: To evaluate various factors affecting the integrity of human donor corneal epithelium. Methods: Donor corneal buttons [...]

Published
2023

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