healthcare technology

As we progress deeper into the digital age, the robust development and application of advanced artificial intelligence (AI) technology, specifically generative language models like ChatGPT (OpenAI), have potential implications in all sectors including medicine.

ChatGPT, a generative language model launched by OpenAI in November 2022 has essentially has essentially revolutionized the IT world.. What makes ChatGPT a promising tool is the vast amounts of data used in its training and its ability to generate human-like conversations covering diverse topics.

The unprecedented capacity of ChatGPT to generate human-like responses, refined through Reinforcement Learning with Human Feedback, could significantly reshape the pedagogical methodologies within medical education.

The use of AI in medicine, including the use of generative language models, is often accompanied by challenges and contentions. Some common challenges include privacy, data security, algorithmic transparency and explainability, errors and liability, as well as regulatory issues associated with AI medicine.

Lately, the use of generative language models in scientific writing has also stirred up controversies in the academic and publishing communities. Some journals have declined ChatGPT as a coauthor, whereas others have happily accepted manuscripts authored by ChatGPT

Through a comprehensive review and the authors’ personal experiences, this viewpoint article elucidates the pros, cons, and ethical considerations of using ChatGPT within clinical medicine and notably, its implications for medical education.

This exploration is crucial in a transformative era where AI could potentially augment human capability in the process of knowledge creation and dissemination, potentially revolutionizing medical education and clinical practice.

The importance of maintaining academic integrity and professional standards is highlighted. The relevance of establishing clear guidelines for the responsible and ethical use of AI technologies in clinical medicine and medical education is also emphasized.

read the whole article at https://mededu.jmir.org/2023/1/e47274

South Korea introduced a new health care IT system named the Narcotics Information Management System (NIMS) with the objective of managing all aspects of opioid use, including manufacturing, distribution, sales, disposal, etc.

The authors conducted an analysis using national claims data from 45,582 patients diagnosed with musculoskeletal and connective tissue disorders between 2016 and 2020.  The approach included using an interrupted time-series analysis and constructing segmented regression models. Within these models, the authors considered the primary intervention to be the implementation of NIMS, while we treated the COVID-19 outbreak as the secondary event.

To comprehensively assess inappropriate opioid use, we examined 4 key indicators, as established in previous studies:

(1) the proportion of patients on high-dose opioid treatment,

(2) the proportion of patients receiving opioid prescriptions from multiple providers,

(3) the overlap rate of opioid prescriptions per patient, and

(4) the naloxone use rate among opioid users.

This study suggests that, in its current form, the NIMS may not have brought significant improvements to the identified indicators of opioid overuse and misuse. Additionally, the COVID-19 outbreak exhibited no significant influence on opioid use patterns.

The absence of real-time monitoring feature within the NIMS could be a key contributing factor. Further exploration and enhancements are needed to maximize the NIMS’ impact on curbing inappropriate opioid use.

read the original at https://publichealth.jmir.org/2024/1/e47130/

Scientists have fabricated a device that can mimic human brain cognitive actions and is more efficient than conventional techniques in emulating artificial intelligence, thus enhancing the computational speed and power consumption efficiency.

Artificial intelligence is now a part of our daily lives, starting from email filters and smart replies in communication to helping battle the Covid-19 pandemic. But AI can do much more such as facilitate self-driving autonomous vehicles, augmented reality for healthcare, drug discovery, big data handling, real-time pattern/image recognition, solving real-world problems, and so on.

These can be realised with the help of a neuromorphic device which can mimic the human brain synapse to bring about brain-inspired efficient computing ability. The human brain comprises of nearly a hundred billion neurons consisting of axons and dendrites. These neurons massively interconnect with each other via axons and dendrites, forming colossal junctions called synapse.

This complex bio-neural network is believed to give rise to superior cognitive abilities.

Software-based artificial neural networks (ANN) can be seen defeating humans in games or helping handle the Covid-19 situation. However, the power-hungry (in megawatts) von Neumann computer architecture slows down ANNs performance due to the available serial processing while the brain does the job via parallel processing consuming just 20 W. It is estimated that the brain consumes 20% of the total body energy. From the calory conversion, it amounts to 20 watts. While the conventional computing platforms consume megawatts, i.e., 1 million watts of energy, to mimic basic human cognition.

To overcome this bottleneck, a hardware-based solution involves an artificial synaptic device that, unlike transistors, could emulate the functions of human brain synapse. Scientists had long been trying to develop a synaptic device that can mimic complex psychological behaviors without the aid of external supporting (CMOS) circuits.

To address this challenge, Scientists from Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, an autonomous institute of the Department of Science & Technology, Government of India, devised a novel approach of fabricating an artificial synaptic network (ASN) resembling the biological neural network via a simple self-forming method (the device structure is formed by itself while heating). This work has been recently published in the journal ‘Materials Horizons’.

“Nature has had an incredible amount of time and diversity to engineer ever new forms and functions through evolution. Learning and emulating new processes, technologies, materials and devices from the nature and biology are the important pathways to the significant advances of the future which will increasingly integrate the worlds of the living with the man-made technologies,” said Prof Ashutosh Sharma, Secretary, DST.

read the original unedited post at https://www.indianext.co.in/2021/06/scientists-develop-efficient-artificial-synaptic-network-that-mimics-human-brain/

The past several decades have seen an alarming spike in communicable disease outbreaks worldwide. Given a confluence of host, virologic, environmental, and human factors, experts agree that the next pandemic could already be on the horizon.

In a globalized world, changes in how people use land and interact with their ecosystems—such as rapid deforestation and agricultural expansion—have resulted in humans and animals coming into more frequent and intense contact with one another, increasing opportunities for what is known as "zoonotic disease spillover."

In the past few years alone, numerous disease outbreaks have had suspected or confirmed zoonotic origin, including mpox (formerly known as monkeypox), Ebola virus disease, dengue fever, and COVID-19.

Experts also recognize the need to prepare for another possible Disease X, a term used to describe a currently unknown pathogen with pandemic potential.

To direct resources toward the most high-consequence pathogens, it is paramount that leaders have an accurate concept of pandemic risk—for individual viruses as well as viral families. Several institutions are developing disease rankings at national and global levels, including the Priority Zoonotic Diseases Lists facilitated by the U.S. Centers for Disease Control and Prevention and the Research and Development (R&D) Blueprint created by the World Health Organization. 

The original SpillOver risk ranking framework (SpillOver 1.0), an open-source webtool launched by researchers at the University of California, Davis One Health Institute, estimated the relative spillover potential of wildlife-origin viruses to humans based on a series of host, viral, and environmental risk factors determined via expert opinion and scientific evidence. 

Its next iteration, SpillOvers 2.0, has rebranded to better describe the diversity and frequency of virus spillovers to people. The new platform uses a One Health approach, which recognizes the interdependence of human, animal, and environmental health. It will expand to include domestic animal and vector-borne viruses and assess pandemic risk rather than just spillover risk for wildlife viruses.

The world of healthcare is ever-evolving. We are learning and growing every day, which means we are also coming up with new ideas, technologies, and practices every day.

what emerging technologies in Health IT are currently shaping the landscape,

and how do they contribute to improved patient outcomes and healthcare delivery?

This Healthcare IT today's article has a collection of opinions from people from the ever growing digital health community.

includes thoughts like

- proactive patient communication and automated text updates for patient approved people

- using adaptive AI for patient communication

- using AI in billing to bring about a fairness to costs

- using ambient documentation to improve patient provider connections in the presence of an EHR

- use of digital therapeutics

amongst others

read the article at

https://www.healthcareittoday.com/2024/02/12/emerging-technologies-shaping-the-health-it-landscape-and-how-they-contribute-to-improving-patient-outcomes-and-healthcare-delivery/