Search Tag: AI
2025 27 Jan
Lung ultrasound (LUS) is increasingly used for diagnosing and monitoring shortness of breath due to its portability, low cost, and lack of radiation exposure. It provides real-time lung assessments and is more accurate than chest radiography in detecting conditions such as pneumonia, pneumothorax, pleural effusion, and pulmonary oedema. LUS is particularly...Read more
2025 24 Jan
Researchers at Emory University have developed an advanced artificial intelligence (AI) model that accurately predicts the need for blood transfusions in non-traumatic ICU patients. Published in Health Data Science , the study tackles longstanding challenges in forecasting transfusion requirements across diverse patient populations with varying medical...Read more
2025 14 Jan
Recent advances in large language models (LLMs) and generative artificial intelligence (AI) have led to the rapid integration of AI tools into research. These tools are now used to assist with literature reviews, data management and analysis, data synthesis, and editing scientific writing. Additionally, many medical journals utilise AI for tasks such...Read more
2025 14 Jan
Acute kidney injury (AKI) often complicates critical illness, with management focusing on supportive care per the Kidney Disease Improving Global Outcomes (KDIGO) guideline due to the lack of specific reversing therapies. Although timely implementation of these guidelines can reduce postoperative moderate and severe AKI, adherence in routine clinical...Read more
2025 07 Jan
Healthcare systems face challenges like increasing patient loads, rising costs, and staff shortages, which hinder consistent, high-quality care. Without integrating artificial intelligence (AI), these issues could worsen, leading to greater disparities in access and care quality. AI offers transformative potential by automating administrative tasks,...Read more
2024 10 Dec
The integration of AI tools into clinical practice is advancing rapidly, but mechanisms to ensure their safety and effectiveness remain insufficient. That is why healthcare organisations (HCOs) and clinicians face challenges in adopting AI responsibly. Risks like model drift, algorithmic errors, biases, and overfitting have already been observed...Read more
2024 04 Nov
Emerging technologies, particularly Artificial Intelligence (AI), are often declared to be transformative in healthcare, with high hopes, expectations, and concerns surpassing those for EHRs, digital health tools, and telemedicine. The FDA has proactively prepared for AI’s integration into healthcare and biomedical product development yet faces distinct...Read more
2024 05 Aug
Medical decision systems powered by artificial intelligence (AI) are widely used in healthcare. The rapid development and commercialisation of these systems outpace the understanding of their clinical value, creating an "AI chasm." This gap is due to various technical and logistical challenges and issues in clinical implementation. The relationship...Read more
2024 30 Jul
On November 30, 2022, OpenAI released ChatGPT, the first chatbot and virtual assistant powered by large language models (LLMs). Within five days, ChatGPT attracted over 1 million users and reached 200 million monthly active users worldwide within fifteen months. This rapid surge in interest transformed artificial intelligence (AI) from a niche...Read more
2024 24 Jul
Researchers at Johns Hopkins Medicine have identified a potential alternative, less-invasive method for measuring intracranial pressure (ICP) in patients. The research is published in Computers in Biology and Medicine. ICP can abnormally increase due to conditions such as acute brain injury, stroke, or cerebrospinal fluid flow obstruction,...Read more
2024 14 Jun
Deploying and evaluating a machine learning intervention to improve clinical care and patient outcomes is a key step in moving clinical deterioration models from byte to bedside. A Mount Sinai study found that hospitalised patients were 43% more likely to have their care escalated and significantly less likely to die if their care team received...Read more
2024 04 Jun
Recent advancements in generative AI have produced large language models (LLMs) capable of writing persuasive articles, passing professional exams, and crafting empathetic messages. While their potential in medicine and healthcare is significant, concerns about their accuracy, reliability, and alignment with human values persist. These concerns...Read more
2024 17 May
Physiological monitoring has a rich 200-year history. In this article, the authors look into the components of an ideal monitoring system and highlight how advancements in modern technology could enable the development of an effective continuous monitoring and response system. The continuous monitoring of patient vital signs is a required...Read more
2024 22 Apr
Intensive care medicine is recognised as a promising field for implementing artificial intelligence (AI) due to the abundance of data generated in intensive care units (ICUs). However, despite the potential benefits, there is a significant gap between developed AI models and their actual clinical use. Challenges include technological issues in...Read more
2024 17 Apr
The increasing availability of complex health data, coupled with advancing computational capabilities, offers an opportunity to define health and disease states with greater clarity and efficiency. This potential extends to real-time diagnosis and patient management. Due to its time-critical nature, the ICU presents unique challenges in creating effective...Read more
2023 30 Nov
This article explores how pervasive and persuasive the internet is in current critical care practice, offers insights into how healthcare professionals, patients and families can critically appraise where information comes from and its content producers and discusses the opportunities and threats posed by AI on the physicians/team-patient/family...Read more
2023 22 Aug
The healthcare industry is seeing remarkable technological progress. Several new tools have emerged that could significantly influence scientific research. One notable tool is RTutor, which combines the R programming language with GPT-3. This integration allows users to create R code and conduct analyses using plain language explanations of data and...Read more
2023 11 Jul
Artificial intelligence (AI) can revolutionise medical publishing. The advantages of AI can be observed in three key areas: content, peer review, and post-publication. AI can enhance each process's speed, accuracy, and efficiency. AI can streamline content creation. It can assist researchers in analysing vast amounts of data, extracting relevant...Read more
2021 06 Jul
Artificial Intelligence (AI) holds great promise in critical care. Vast amounts of data are regularly collected in intensive care units, making ICUs the perfect environment for deploying machine-learning techniques. AI in ICUs can have several applications. For example, when determining the short and long-term outcomes of different interventions,...Read more
2021 22 Feb
Why digitalisation of intensive care medicine means less rather than more data Intensive Care Medicine is generating an amount of data that is hardly analysable by humans. Digitalising and using artificial intelligence has to focus on providing less rather than more data. Introduction - AI in Intensive Care Medicine: Ghost or Glimmer...Read more
2021 22 Feb
Perioperative cardiorespiratory compromise is common and goes largely undetected. Predictive cardiorespiratory indices can help in early detection of harmful deviations and guide preemptive treatment. Using continuous cardiorespiratory monitoring coupled with these tools, we now know which patients are likely to decompensate both within and outside...Read more
2020 26 Feb
With the introduction of computers and advanced technology, the majority of patient data is now captured digitally. And this has allowed opportunities for machine learning. Today, machine learning is frequently used to make diagnosis or predict disease outcomes, optimise treatment decisions and determine the prognosis of patients. While there...Read more
2020 15 Jan
An AI-enabled ICU is coming in the not-too-distant future, but it requires strong partnerships between clinicians and engineers. Spoiler alert. The short answer to this question is yes! Artificial Intelligence in Medicine” has been taking place biannually for the past 28 years (Patel et al. 2009). What is new, however, is the...Read more
2020 15 Jan
Over the next 50 years, critical care will evolve from a system that reacts to patient deterioration into a system that predicts and prevents these events. The application of real-time analytics to large-scale integrated ICU patient data will facilitate creation of learning healthcare systems and delivery of personalised and even predictive critical...Read more
2019 01 Nov
Each year, Emergency Departments (ED) across the United States see more than 145 million visits, according to Centers for Disease Control and Prevention data. Nearly two-and-a-half million ED patients end up getting some kind of diagnostic exam, like ultrasound, that confirms if a hospital stay is needed. In highly populated areas, doctors often struggle...Read more
2019 20 Mar
At this years 39th International Symposium on Intensive Care and Emergency Medicine , Professor Jerry Nolan , a consultant in anaesthesia and intensive care medicine at the Royal United Hospital, Bath, talked about new developments in CPR during the Max Harry Weil Lecture, one of the most important presentations at #ISICEM19. Dr. Max Harry Weil...Read more
2019 27 Feb
The increasing number of emergency department (ED) visits often correlates with ED crowding and delays in care. This problem highlights the need for ED triage systems that accurately differentiate and prioritise critically ill from stable patients, enabling efficient allocation of finite ED resources. Currently, the Emergent Severity...Read more