Deep Learning and its Application for Healthcare Delivery in Low and Middle Income Countries

Williams, Douglas; Hornung, Heiko; Nadimpalli, Adi; Peery, Ashton

doi:10.3389/frai.2021.553987

Cited by 29 publications

(10 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, countries in the Global South, which often face a dearth of medical professionals, could immensely benefit from AI-supported diagnostics, such as deep-learning algorithms for segmenting and classifying chest X-rays. 41 , 42 Yet, the usefulness of these tools is contingent on their accuracy and representativeness. 43 If the training data for medical AI tools is predominantly sourced from the Global North, there is a risk that algorithms are performing poorer in recognizing certain conditions inherent to other patient demographics.…”

Section: Discussionmentioning

confidence: 99%

Mapping gender and geographic diversity in artificial intelligence research: Editor representation in leading computer science journals

Busch,

Keller,

Rueger

et al. 2023

Acta Radiologica Open

View full text Add to dashboard Cite

Background The growing role of artificial intelligence (AI) in healthcare, particularly radiology, requires its unbiased and fair development and implementation, starting with the constitution of the scientific community. Purpose To examine the gender and country distribution among academic editors in leading computer science and AI journals. Material and Methods This cross-sectional study analyzed the gender and country distribution among editors-in-chief, senior, and associate editors in all 75 Q1 computer science and AI journals in the Clarivate Journal Citations Report and SCImago Journal Ranking 2022. Gender was determined using an open-source algorithm (Gender Guesser™), selecting the gender with the highest calibrated probability. Result Among 4,948 editorial board members, women were underrepresented in all positions (editors-in-chief/senior editors/associate editors: 14%/18%/17%). The proportion of women correlated positively with the SCImago Journal Rank indicator (ρ = 0.329; p = .004). The U.S., the U.K., and China comprised 50% of editors, while Australia, Finland, Estonia, Denmark, the Netherlands, the U.K., Switzerland, and Slovenia had the highest women editor representation per million women population. Conclusion Our results highlight gender and geographic disparities on leading computer science and AI journal editorial boards, with women being underrepresented in all positions and a disproportional relationship between the Global North and South.

show abstract

Section: Discussionmentioning

confidence: 99%

Mapping gender and geographic diversity in artificial intelligence research: Editor representation in leading computer science journals

Busch,

Keller,

Rueger

et al. 2023

Acta Radiologica Open

View full text Add to dashboard Cite

show abstract

“…The three terms "artificial intelligence,""machine learning," and "deep learning" can occasionally be used interchangeably, which frequently causes misunderstanding among nontechnologists [40]. The phrase "artificial intelligence" refers to a vast, established, and highly developed area of computer science study that addresses issues relating to machine intelligence, such as simulating cognitive functions, detecting the environment, and acting independently.…”

Section: Ai Approachesmentioning

confidence: 99%

Challenges and Prospective of AI and 5G-Enabled Technologies in Emerging Applications during the Pandemic

Rahman¹,

Khatun²

2023

Artificial Intelligence

View full text Add to dashboard Cite

5G is being implemented in the Internet of things (IoT) era. This book chapter focuses on 5G technology and the integration of other digital technologies, such as artificial intelligence (AI) and machine learning, IoT, big data analytics, cloud computing, robotics, and other digital platforms into new healthcare applications. Now, the healthcare industry is implementing 5G-enabled technology to improve health services, medical research, quality of life, and medical professionals’ and patients’ experiences everywhere, at any time. Technology can facilitate faster medical research progress and better clinical and social services management. Furthermore, AI approaches with 5G connectivity may be able to combat the epidemic challenges with minimal resources. This book chapter underlines how 5G technology is growing to address epidemic concerns. The study highlights many technical issues and future developments for creating 5G-powered healthcare solutions. This chapter also addresses the key challenges AI and 5G technology face in emerging healthcare solutions. In addition, this book chapter highlights perspective, policy recommendations, and future research directions of AI and 5G-enabled technologies in confronting future pandemics. More research will be incorporated into future projects, including studies on developing a digital society based on 5G technology in healthcare emergencies.

show abstract

“…Machine learning and deep learning have played an important role in the field of medical image processing where machine learning algorithms have been used to classify Covid-19 affected individuals (Bhattacharya et al, 2021) and classifying the severity of Covid-19 diagnosed patient using neuro fuzzy techniques (Ayoub et al, 2021;Iwendi et al, 2021). Another study on how deep learning is being used for healthcare delivery in low and middle income countries has been done where the authors have explained how pneumonia detection using state-of-the-art deep learning algorithms can be utilized to help those countries with limited facilities and resources (Williams et al, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Deep Learning-based Sentiment Analysis and Topic Modeling on Tourism During Covid-19 Pandemic

Mishra

Urolagin

Jothi

et al. 2021

Front. Comput. Sci.

View full text Add to dashboard Cite

The Covid-19 pandemic has disrupted the world economy and significantly influenced the tourism industry. Millions of people have shared their emotions, views, facts, and circumstances on numerous social media platforms, which has resulted in a massive flow of information. The high-density social media data has drawn many researchers to extract valuable information and understand the user’s emotions during the pandemic time. The research looks at the data collected from the micro-blogging site Twitter for the tourism sector, emphasizing sub-domains hospitality and healthcare. The sentiment of approximately 20,000 tweets have been calculated using Valence Aware Dictionary for Sentiment Reasoning (VADER) model. Furthermore, topic modeling was used to reveal certain hidden themes and determine the narrative and direction of the topics related to tourism healthcare, and hospitality. Topic modeling also helped us to identify inter-cluster similar terms and analyzing the flow of information from a group of a similar opinion. Finally, a cutting-edge deep learning classification model was used with different epoch sizes of the dataset to anticipate and classify the people’s feelings. The deep learning model has been tested with multiple parameters such as training set accuracy, test set accuracy, validation loss, validation accuracy, etc., and resulted in more than a 90% in training set accuracy tourism hospitality and healthcare reported 80.9 and 78.7% respectively on test set accuracy.

show abstract

Deep Learning and its Application for Healthcare Delivery in Low and Middle Income Countries

Cited by 29 publications

References 25 publications

Mapping gender and geographic diversity in artificial intelligence research: Editor representation in leading computer science journals

Mapping gender and geographic diversity in artificial intelligence research: Editor representation in leading computer science journals

Challenges and Prospective of AI and 5G-Enabled Technologies in Emerging Applications during the Pandemic

Deep Learning-based Sentiment Analysis and Topic Modeling on Tourism During Covid-19 Pandemic

Contact Info

Product

Resources

About