(Press-News.org) (Toronto, May 20, 2025) JMIR Publications invites submissions to a new theme issue titled “Opportunities and Challenges in the Applications of AI In Public Health Informatics” in its open access journal Online Journal of Public Health Informatics. The premier, peer-reviewed journal is indexed in PubMed, PubMed Central (PMC), DOAJ, Sherpa/Romeo, Web of Science Core Collection: Emerging Sources Citation Index and Scopus.
The application of artificial intelligence (AI) in public health informatics presents both significant challenges and opportunities. AI has the potential to revolutionize public health by enabling better data collection and analysis, enhancing disease surveillance, improving decision-making, and strengthening public health interventions. However, its implementation also faces technical, ethical, and operational challenges. To further leverage AI’s contribution to public health issues, it is crucial to address concerns regarding health equity, privacy and security, transparency and explainability, accountability and governance, data quality and interoperability, and bias in AI models.
The integration of AI applications into precision public health empowers health professionals to target interventions to specific communities based on social determinants of health. This transition from a broad, one-size-fits all approach to a community-based intervention leads to more efficient management of infectious diseases, reduction of health care costs, and improvements in overall population health outcomes. Human-AI collaboration at the community level is required for the successful integration of AI into precision public health.
This issue invites researchers, practitioners, and policymakers to submit thought-provoking works on topics including, but not limited to, the following key themes:
Data privacy and security: concerns about confidentiality, consent, and regulatory compliance
Bias in AI models: training AI models on non-representative health data can result in inequitable outcomes
Ethical considerations: ethical dilemmas in making decisions about resource allocation and prioritization of interventions
Data preparation for AI applications: adherence to FAIR (Findable, Accessible, Interoperable, and Reusable) principles for digital assets, enabling their transformation into AI-ready formats
Disease detection and surveillance: real-time outbreak prediction and detection of emerging public health threats
To learn more please visit the website.
About JMIR Publications
JMIR Publications is a leading open access publisher of digital health research and a champion of open science. With a focus on author advocacy and research amplification, JMIR Publications partners with researchers to advance their careers and maximize the impact of their work. As a technology organization with publishing at its core, we provide innovative tools and resources that go beyond traditional publishing, supporting researchers at every step of the dissemination process. Our portfolio features a range of peer-reviewed journals, including the renowned Journal of Medical Internet Research.
END
The Online Journal of Public Health Informatics invites submissions on opportunities and challenges in the applications of AI in public health informatics
2025-05-20
ELSE PRESS RELEASES FROM THIS DATE:
Thousands of animal species threatened by climate change, novel analysis finds
2025-05-20
CORVALLIS, Ore. – A novel analysis suggests more than 3,500 animal species are threatened by climate change and also sheds light on huge gaps in fully understanding the risk to the animal kingdom.
The study was published today in BioScience.
“We’re at the start of an existential crisis for the Earth’s wild animals,” said Oregon State University’s William Ripple, who led the study. “Up till now, the primary cause of biodiversity loss has been the twin threats of overexploitation and habitat alteration, but as climate change intensifies, we expect it to become a third ...
Shorter MRI exam effectively detects cancer in dense breasts
2025-05-20
OAK BROOK, Ill. – Abbreviated breast MRI shortens exam time while retaining a high level of diagnostic accuracy of breast cancer in women with extremely dense breasts, according to an article published today in Radiology, a journal of the Radiological Society of North America (RSNA).
Women with extremely dense breasts have a high proportion of dense glandular and fibrous tissue and very little fatty tissue. This can be a risk factor for breast cancer due to the similar appearance of tumors and dense breast tissue on mammograms.
Supplemental MRI screening is generally recommended for women with extremely dense ...
Radiologists share tips to prevent AI bias
2025-05-20
OAK BROOK, Ill. – Radiologists, computer scientists and informaticists outline pitfalls and best practices to mitigate bias in artificial intelligence (AI) models in an article published today in Radiology, a journal of the Radiological Society of North America (RSNA).
“AI has the potential to revolutionize radiology by improving diagnostic accuracy and access to care,” said lead author Paul H. Yi, M.D., associate member (associate professor) in the Department of Radiology and director of Intelligent Imaging Informatics at ...
Fine-tuned LLMs boost error detection in radiology reports
2025-05-20
OAK BROOK, Ill. – A type of artificial intelligence called fine-tuned large language models (LLMs) greatly enhances error detection in radiology reports, according to a new study published today in Radiology, a journal of the Radiological Society of North America (RSNA). Researchers said the findings point to an important role for this technology in medical proofreading.
Radiology reports are crucial for optimal patient care. Their accuracy can be compromised by factors like errors in speech recognition software, variability ...
Climate change emerges as third major threat to global wildlife, scientists warn
2025-05-20
New research published in BioScience reveals that climate change is rapidly emerging as a third major threat to Earth's wild animals, joining habitat alteration and overexploitation in what scientists call a shift from "twin to triple threats."
The research team, led by William J. Ripple of Oregon State University, analyzed data for 70,814 animal species from 35 classes, using two publicly available biodiversity datasets to assess climate change vulnerability among the world's wild animal populations.
Their ...
New blood test developed at Mass General Brigham shows superior sensitivity in detecting HPV-associated head and neck cancers
2025-05-20
A new liquid biopsy blood test could help detect cases of human papillomavirus (HPV)-associated head and neck cancers with significantly higher accuracy than currently used methods, including before patients develop symptoms, according to new Mass General Brigham research.
The researchers at Mass Eye and Ear, a member of the Mass General Brigham healthcare system, found that the blood-based diagnostic test they developed called HPV-DeepSeek achieved 99% sensitivity and 99% specificity for diagnosing cancer at the time of first clinical presentation, including ...
The hidden drivers of aging: microbial influence on genomic stability and telomere dynamics
2025-05-20
Aging is a multifaceted process driven by interconnected biological mechanisms, among which genomic instability and telomere attrition stand as primary hallmarks. Emerging research underscores the pivotal role of the human microbiome in modulating these processes, offering novel insights into aging and age-related diseases. This review synthesizes current evidence on how microbial dysbiosis accelerates aging by disrupting genomic integrity and telomere dynamics, while also exploring therapeutic strategies to promote healthy ...
Neurosymbolic AI could be leaner and smarter
2025-05-20
Could AI that thinks more like a human be more sustainable than today’s LLMs? The AI industry is dominated by large companies with deep pockets and a gargantuan appetite for energy to power their models’ mammoth computing needs. Data centers supporting AI already account for up to 3.7% of global greenhouse emissions. In a Perspective, Alvaro Velasquez and colleagues propose an alternative model: neurosymbolic AI, which would require far less computing power, creating opportunities for smaller players to enter the field and allowing society to enjoy the benefits of AI without the environmental costs. Neurosymbolic AI is built on data-driven neural ...
Intuition-guided reinforcement learning for soft tissue manipulation with unknown constraints
2025-05-20
A research paper by scientists at Hefei University of Technology presented an intuition-guided deep reinforcement learning framework for soft tissue manipulation under unknown constraints.
The research paper, published on Apr. 14, 2025 in the journal Cyborg and Bionic Systems.
Intraoperative soft tissue manipulation is a critical challenge in autonomous robotic surgery. Furthermore, the intricate in vivo environment surrounding the target soft tissues poses additional hindrances to autonomous robotic decision-making. Previous studies assumed the grasping point was known and the target deformation could be achieved. The constraints were assumed to be constant during the ...
Mount Sinai surgeons perform first heart-liver-kidney transplants in New York State
2025-05-20
A team of Mount Sinai surgeons has performed the first heart-liver-kidney triple organ transplants in New York. They successfully completed two of these complex surgeries on patients from Westchester County, who have since returned home and are making full recoveries.
Heart-liver-kidney transplants are extremely rare—only 58 have been done across the country since the United Network for Organ Sharing, the government agency that oversees transplantation, started tracking cases in 1987. The two procedures at The Mount Sinai Hospital, which took place on January 10 and March 8, were among only four to date in the ...