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BMJ Digital Health & AI

BMJ

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1

Add abstracts to 22 articles

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Medium impact22 DOIs
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DOIs for this ISSN

Showing the top 5 of 81 DOIs, ordered by correction priority.

# Title Missing Priority Citations
1 Welcome to <i>BMJ Digital Health &amp; A… (10.1136/bmjdhai-2024-000004)
Abstract References ORCID
22.58 1
2 Identifying and understanding significant change due to drif… (10.1136/bmjdh-2026-000085)
ORCID
11.93 2
3 Engaging patients in AI governance (10.1136/bmjdh-2026-000099)
Abstract
7.53 1
4 Mind the gap: aligning clinician and patient priorities in d… (10.1136/bmjdhai-2025-000097)
Abstract
7.53 1
5 Digital morphine: why AI scribes are symptomatic relief for… (10.1136/bmjdh-2026-000030)
Abstract
0.00 0
6 Utilising the digital twin for disease prevention, treatment… (10.1136/bmjdh-2026-000031)
Abstract
0.00 0
7 Context is key: context engineering as the next frontier of… (10.1136/bmjdh-2026-000032)
Abstract
0.00 0
8 Machine learning for prediction of weaning and extubation fr… (10.1136/bmjdh-2026-000033)
0.00 0
9 Comparison of three large language models' ability to assess… (10.1136/bmjdh-2026-000034)
0.00 0
10 Use of artificial intelligence in the out-of-hospital care s… (10.1136/bmjdh-2026-000035)
0.00 0
11 What can chatbot conversations reveal about vaccine concerns… (10.1136/bmjdh-2026-000036)
ORCID
0.00 0
12 Machine-learning approach to dissect the clinical heterogene… (10.1136/bmjdh-2026-000037)
0.00 0
13 When medical AI fails outside English (10.1136/bmjdh-2026-000038)
Abstract
0.00 0
14 Does ambient voice technology in healthcare really save time… (10.1136/bmjdh-2026-000039)
Abstract
0.00 0
15 COPE: Chain-of-Thought Prediction Engine for open-source lar… (10.1136/bmjdh-2026-000040)
0.00 0
16 Analysis of the challenges in ensuring robust and effective… (10.1136/bmjdh-2026-000043)
0.00 0
17 From bedside to bench: towards clinical predictive AI resear… (10.1136/bmjdh-2026-000044)
0.00 0
18 Clinical deskilling in the age of artificial intelligence: a… (10.1136/bmjdh-2026-000045)
Abstract
0.00 0
19 Computer-aided polyp detection and characterisation systems… (10.1136/bmjdh-2026-000046)
0.00 0
20 Academia and industry in the age of artificial intelligence:… (10.1136/bmjdh-2026-000047)
0.00 0
21 Understanding digital inclusion through the transformation o… (10.1136/bmjdh-2026-000051)
0.00 0
22 Why health AI needs protocols, not just pilots (10.1136/bmjdh-2026-000052)
Abstract
0.00 0
23 Why are humans still in the loop with advancing AI capabilit… (10.1136/bmjdh-2026-000057)
Abstract ORCID
0.00 0
24 Meeting clinicians where they are through signal-guided AI i… (10.1136/bmjdh-2026-000064)
Abstract
0.00 0
25 Machine learning–based prediction of Metabolic Syndrome risk… (10.1136/bmjdh-2026-000065)
0.00 0
26 Predicting the causes of unplanned reoperations using an AI-… (10.1136/bmjdh-2026-000066)
0.00 0
27 Machine learning-based prediction of bacterial infection foc… (10.1136/bmjdh-2026-000068)
0.00 0
28 Predicting wound healing outcomes: a comparative accuracy an… (10.1136/bmjdh-2026-000069)
ORCID
0.00 0
29 Harnessing patient health data to benefit individuals and ad… (10.1136/bmjdh-2026-000070)
0.00 0
30 Artificial intelligence-assisted reader evaluation in acute… (10.1136/bmjdh-2026-000071)
ORCID
0.00 0
31 ‘…it helps me to be able to do the right thing …’: pilot of… (10.1136/bmjdh-2026-000073)
0.00 0
32 Developing the i-MoMCARE application in Cambodia: an iterati… (10.1136/bmjdh-2026-000074)
0.00 0
33 Predicting cardiac index from coronary angiogram videos: a n… (10.1136/bmjdh-2026-000080)
0.00 0
34 From iPatient to Ai-Patient: a responsibility to medical edu… (10.1136/bmjdh-2026-000082)
Abstract
0.00 0
35 Responsible AI UK: priorities for delivering England’s healt… (10.1136/bmjdh-2026-000083)
Abstract
0.00 0
36 Using a novel hybrid AI-based paper-to-digital pipeline for… (10.1136/bmjdh-2026-000092)
0.00 0
37 Drift isn’t a bug, it’s the work: post-deployment surveillan… (10.1136/bmjdh-2026-000111)
Abstract
0.00 0
38 Introducing <i>BMJ Connections Digital H… (10.1136/bmjdh-2026-000156)
Abstract References
0.00 0
39 Healthcare professionals’ views on implementing digital heal… (10.1136/bmjdhai-2025-000005)
0.00 2
40 Establishment and validation of an artificial intelligence-b… (10.1136/bmjdhai-2025-000010)
0.00 0
41 The AI loop: redefining medical research from data to clinic… (10.1136/bmjdhai-2025-000013)
Abstract
0.00 0
42 Optimising large language models for clinical information ex… (10.1136/bmjdhai-2025-000014)
0.00 2
43 Large language model enhanced framework for systematic revie… (10.1136/bmjdhai-2025-000017)
0.00 0
44 Next-generation wearable sensors for biopsychosocial care in… (10.1136/bmjdhai-2025-000018)
0.00 6
45 INSIGHTFUL: insight generation through clinical annotation,… (10.1136/bmjdhai-2025-000019)
0.00 1
46 Interpretable machine learning-based detection of coeliac di… (10.1136/bmjdhai-2025-000023)
0.00 3
47 High-accuracy ECG image interpretation using parameter-effic… (10.1136/bmjdhai-2025-000031)
0.00 1
48 Patterns of online consultation use in Great Britain, 2019–2… (10.1136/bmjdhai-2025-000032)
0.00 2
49 Can generative AI assess PTSD? A clinical validation study o… (10.1136/bmjdhai-2025-000042)
0.00 1
50 Importance of model governance in clinical AI models: case s… (10.1136/bmjdhai-2025-000046)
0.00 13