Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar et al.
Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 infection with high accuracy can be crucially helpful to the healthcare professio...
Md. Mostafizer Rahman, Yutaka Watanobe
In recent years, the rise of advanced artificial intelligence technologies has had a profound impact on many fields, including education and research. One such technology is ChatGPT, a powerful large language model developed by OpenAI. This technology offers exciting opportunities for students and e...
Md Manjurul Ahsan, Shahana Akter Luna, Zahed Siddique
Globally, there is a substantial unmet need to diagnose various diseases effectively. The complexity of the different disease mechanisms and underlying symptoms of the patient population presents massive challenges in developing the early diagnosis tool and effective treatment. Machine learning (ML)...
Angela Zhang, Lei Xing, James Zou, Joseph C. Wu
In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements in clinical capabilities and access to care. This progress has emphasized that, from model development to model deployment, data play central roles. I...
Abdullahi Yusuf, Nasrin Pervin, Marcos Román-González
Abstract In recent years, higher education (HE) globally has witnessed extensive adoption of technology, particularly in teaching and research. The emergence of generative Artificial Intelligence (GenAI) further accelerates this trend. However, the increasing sophistication of GenAI tools has raised...
Anichur Rahman, Md. Sazzad Hossain, Ghulam Muhammad, Dipanjali Kundu et al.
Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare field. Traditionally, the healthcare system works based on centralized agents sharing their raw data. Therefore, huge vulne...
Zhi Zhen Qin, Shahriar Ahmed, Mohammad Shahnewaz Sarker, Kishor Kumar Paul et al.
BACKGROUND: Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI algorithms are available commercially, yet there is little impartial evidence on how their performance compares with each other and with radiologists. W...
Priti Tagde, Sandeep Tagde, Tanima Bhattacharya, Pooja Tagde et al.
Blockchain and artificial intelligence technologies are novel innovations in healthcare sector. Data on healthcare indices are collected from data published on Web of Sciences and other Google survey from various governing bodies. In this review, we focused on various aspects of blockchain and artif...
Md. Mizanur Rahman, Harold Jan R. Terano, Md Nafizur Rahman, Aidin Salamzadeh et al.
In the academic world, academicians, researchers, and students have already employed Large Language Models (LLMs) such as ChatGPT to complete their various academic and non-academic tasks, including essay writing, different formal and informal speech writing, summarising literature, and generating i...
Sujan Sarker, Lafifa Jamal, Syeda Faiza Ahmed, Niloy Irtisam
The outbreak of the COVID-19 pandemic is unarguably the biggest catastrophe of the 21st century, probably the most significant global crisis after the second world war. The rapid spreading capability of the virus has compelled the world population to maintain strict preventive measures. The outrage ...
Anichur Rahman, Tanoy Debnath, Dipanjali Kundu, Md. Saikat Islam Khan et al.
In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given the current progress in the fields of ML and...
Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder
Artificial intelligence (AI) models are increasingly finding applications in the field of medicine. Concerns have been raised about the explainability of the decisions that are made by these AI models. In this article, we give a systematic analysis of explainable artificial intelligence (XAI), with ...
Moustaq Karim Khan Rony, Mst. Rina Parvin, Silvia Ferdousi
AIM: This article aimed to explore the role of AI in advancing nursing practice, focusing on its impact on readiness for the future. DESIGN AND METHODS: A position paper, the methodology comprises three key steps. First, a comprehensive literature search using specific keywords in reputable database...
Moustaq Karim Khan Rony, Ibne Kayesh, Shuvashish Das Bala, Fazila Akter et al.
Background: The healthcare landscape is rapidly evolving, with artificial intelligence (AI) emerging as a transformative force. In this context, understanding the viewpoints of nursing professionals regarding the integration of AI in future nursing care is crucial. Aims: This study aimed to provide ...
Joseph Ana, Tracey Pérez Koehlmoos, Richard Smith, Lijing L. Yan
As part of a cluster of articles critically reflecting on the theme of "no health without research," Richard Smith and colleagues lay out what is currently known about research misconduct in low- and middle-income countries, summarizing some high profile cases and making suggestions on ways forward.