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From iPatient to Ai-Patient: a responsibility to medical education
Our institution was an early implementer of a major electronic health record (EHR) in 2008. Trainees immediately restructured their workflows around the computer, no longer required to manually transc …
A comprehensive public health approach is needed to study the impact of digital technology on health
Barely a day goes by without media and political concern about the impact of digital technology on health, particularly among young people. The publication of a recent government report, “Understandin …
New risk prediction model for managing COPD in primary care
Tool offers increased precision in estimating exacerbation risk Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. It is frequently seen in primary c …
Charles Polkey: neurosurgeon and pioneer of the surgical treatment of epilepsy
When the powers that be at King’s College Hospital told neurosurgeon Charles Polkey that it had decided to name a ward after him he was initially reluctant to accept the honour. He only relented after …
MyChart: doctors are left frustrated and patients panic as NHS trusts roll out hospital records app
US tech giant Epic’s hospital records portal has been rolled out by NHS trusts in England. But amid poor integration with the NHS App and low user literacy, users say it causes as many problems as it …
Palantir: Coalition urges NHS organisations to refuse to use controversial tech giant’s software
Every hospital in England has been urged to disobey an NHS directive to use software operated by controversial US analytics software company Palantir. A coalition of human rights, health and patient o …
“Technostress”—the NHS is overloading doctors with devices
Doctors are carrying more and more hardware. Each device is designed to do a job, but together they are giving clinicians “alarm fatigue”—to the detriment of patient safety. Chris Stokel-Walker report …
Getting published: ask editor Helen Surana

Getting published: ask editor Helen Surana

27 Mar 2026 BMJ Future Health
What was your journey to becoming co-editor-in-chief of BMJ Innovations? I’m a classic portfolio doctor, and have spent a lot of my career at BMJ Group. I’ve worked on BMJ Learning, BMJ Best Practice, …
Meet Dr Tamsin Holland Brown

Meet Dr Tamsin Holland Brown

27 Mar 2026 BMJ Future Health
Three years ago, Modesta Bene, aged 13, failed her school exams in rural Malawi. No one knew it yet, but Modesta was capable. She just couldn't hear. In January 2020, a Malawian doctor diagnosed Modes …
Ask the editor: 60 seconds with Dr Felix Holl
BMJ Group recently launched BMJ Connections Digital Health & AI, an open-access journal that sits alongside BMJ Digital Health & AI.  Both journals publish original research, but the Connections journ …
Mobile-accessible deep learning-based self-assessment tool for measles screening in low-resource settings
What is already known on this topic Measles is highly contagious and poses serious health risks, particularly to young children. Global vaccination coverage declined in 2023, with only 83% receiving t …
Priorities for artificial intelligence education: clinicians’ perspectives
Clinicians are most likely to be motivated to learn about AI framed around its liability implications and determining appropriate confidence in AI algorithms, as these are perceived as important and c …
The impact of skin tone on performance of pulse oximeters used by NHS England COVID Oximetry @home scheme: measurement and diagnostic accuracy study
Arterial haemoglobin oxygen saturation (SaO2) indicates the fraction of oxygenated haemoglobin, relative to total haemoglobin, in arterial blood and provides a useful indicator of hypoxaemia (low bloo …
Déjà vu in healthcare AI: lessons from the world’s pioneer AI clinical decision support system
Recent advances in artificial intelligence (AI) have renewed interest in the possibility of computers assisting, or even replacing, doctors in making clinical decisions. However, computerised clinical …
Impact of acoustic and informational noise on AI-generated clinical summaries
The CAIS generally excelled at capturing a doctor-patient consultation and producing accurate clinical summaries; however, error rate (especially omissions) increased notably when acoustic noise was i …
Clinical AI Scribes in primary care: accuracy, error severity and implications for clinical practice
The CAISs demonstrate high levels of summarisation accuracy. However, there is great disparity between the currently available CAIS products and, while some perform well, none are perfect. Clinicians …
Predicting cardiovascular events from routine mammograms using machine learning
A deep learning algorithm based on only mammographic features and age predicted cardiovascular risk with performance comparable to traditional cardiovascular risk equations. Risk assessments based on …
Early clinical evaluation of a machine-learning system for risk prediction of trauma-induced coagulopathy in the prehospital setting
Early after injury, an ML system performs well compared with expert prehospital clinicians in the prediction of TIC and blood transfusion. The study suggests that ML systems may augment clinical risk …
“How long until I am seen, doc?” Modelling paediatric emergency department waiting times to make personalised predictions
Tailored models created using routine data can be used to give individualised predictions for wait times in paediatric ED, which could be given to patients with the aim of managing expectations and im …
Transforming women’s health through innovation
This BMJ Collection, developed in partnership with Bill and Melinda Gates Foundation, consists of 11 papers. It provides analysis and commentary on the growing global women's health innovation movemen …