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  • Journal article
    Runciman M, Avery J, Zhao M, Darzi A, Mylonas GPet al., 2020,

    Deployable, variable stiffness, cable driven robot for minimally invasive surgery

    , Frontiers in Robotics and AI, Vol: 6, Pages: 1-16, ISSN: 2296-9144

    Minimally Invasive Surgery (MIS) imposes a trade-off between non-invasive access and surgical capability. Treatment of early gastric cancers over 20 mm in diameter can be achieved by performing Endoscopic Submucosal Dissection (ESD) with a flexible endoscope; however, this procedure is technically challenging, suffers from extended operation times and requires extensive training. To facilitate the ESD procedure, we have created a deployable cable driven robot that increases the surgical capabilities of the flexible endoscope while attempting to minimize the impact on the access that they offer. Using a low-profile inflatable support structure in the shape of a hollow hexagonal prism, our robot can fold around the flexible endoscope and, when the target site has been reached, achieve a 73.16% increase in volume and increase its radial stiffness. A sheath around the variable stiffness structure delivers a series of force transmission cables that connect to two independent tubular end-effectors through which standard flexible endoscopic instruments can pass and be anchored. Using a simple control scheme based on the length of each cable, the pose of the two instruments can be controlled by haptic controllers in each hand of the user. The forces exerted by a single instrument were measured, and a maximum magnitude of 8.29 N observed along a single axis. The working channels and tip control of the flexible endoscope remain in use in conjunction with our robot and were used during a procedure imitating the demands of ESD was successfully carried out by a novice user. Not only does this robot facilitate difficult surgical techniques, but it can be easily customized and rapidly produced at low cost due to a programmatic design approach.

  • Journal article
    McKinney SM, Sieniek M, Godbole V, Godwin J, Antropova N, Ashrafian H, Back T, Chesus M, Corrado GC, Darzi A, Etemadi M, Garcia-Vicente F, Gilbert FJ, Halling-Brown M, Hassabis D, Jansen S, Karthikesalingam A, Kelly CJ, King D, Ledsam JR, Melnick D, Mostofi H, Peng L, Reicher JJ, Romera-Paredes B, Sidebottom R, Suleyman M, Tse D, Young KC, De Fauw J, Shetty Set al., 2020,

    International evaluation of an AI system for breast cancer screening

    , Nature, Vol: 577, Pages: 89-94, ISSN: 0028-0836

    Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful1. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives2. Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening.

  • Conference paper
    Zhao M, Oude Vrielink J, Kogkas A, Runciman M, Elson D, Mylonas Get al., 2020,

    LaryngoTORS: A Novel Cable-Driven Parallel Robot for Transoral Laser Surgery

    , International Conference on Robotics and Automation (ICRA)
  • Conference paper
    Leiloglou M, Gkouzionis I, Avila-Rencoret FB, Chalau V, Kedrzycki M, Darzi A, Leff DR, Elson DSet al., 2020,

    Snapshot hyperspectral system for breast conserving surgery guidance

    There is an unmet need for accurate tumour localization in vivo during breast conserving surgery. Herein a novel snapshot hyperspectral system is presented for accurately detecting the intrinsic fluorescence signal in real-time fluorescence guided surgery.

  • Journal article
    Fontana G, Ghafur S, Torne L, Goodman J, Darzi Aet al., 2020,

    Ensuring that the NHS realises fair financial value from its data

    , The Lancet Digital Health, Vol: 2, Pages: e10-e12, ISSN: 2589-7500
  • Journal article
    Harkanen M, Vehvilainen-Julkunen K, Murrells T, Paananen J, Franklin BD, Rafferty AMet al., 2020,

    The Contribution of Staffing to Medication Administration Errors: A Text Mining Analysis of Incident Report Data

    , JOURNAL OF NURSING SCHOLARSHIP, Vol: 52, Pages: 113-123, ISSN: 1527-6546
  • Journal article
    Markiewicz O, Lavelle M, Lorencatto F, Judah G, Ashrafian H, Darzi Aet al., 2020,

    Threats to safe transitions from hospital to home: a consensus study in North West London primary care

    , British Journal of General Practice, Vol: 70, Pages: e9-e19, ISSN: 0960-1643

    Background Transitions between healthcare settings are vulnerable points for patients.Aim To identify key threats to safe patient transitions from hospital to primary care settings.Design and setting Three-round web-based Delphi consensus process among clinical and non-clinical staff from 39 primary care practices in North West London, England.Method Round 1 was a free-text idea-generating round. Rounds 2 and 3 were consensus-obtaining rating rounds. Practices were encouraged to complete the questionnaires at team meetings. Aggregate ratings of perceived level of importance for each threat were calculated (1–3: ‘not important’, 4–6: ‘somewhat important’, 7–9: ‘very important’). Percentage of votes cast for each patient or medication group were recorded; consensus was defined as ≥75%.Results A total of 39 practices completed round 1, 36/39 (92%) completed round 2, and 30/36 (83%) completed round 3. Round 1 identified nine threats encompassing problems involving communication, service organisation, medication provision, and patients who were most at risk. ‘Poor quality of handover instructions from secondary to primary care teams’ achieved the highest rating (mean rating at round 3 = 8.43) and a 100% consensus that it was a ‘very important’ threat. Older individuals (97%) and patients with complex medical problems taking >5 medications (80%) were voted the most vulnerable. Anticoagulants (77%) were considered to pose the greatest risk to patients.Conclusion This study identified specific threats to safe patient transitions from hospital to primary care, providing policymakers and healthcare providers with targets for quality improvement strategies. Further work would need to identify factors underpinning these threats so that interventions can be tailored to the relevant behavioural and environmental contexts in which these threats arise.

  • Journal article
    Geeson C, Wei L, Franklin BD, 2020,

    High-risk medicines associated with clinically relevant medication-related problems in UK hospitals: A prospective observational study

    , BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, Vol: 86, Pages: 165-169, ISSN: 0306-5251
  • Book chapter
    Vrielink TJCO, Vitiello V, Mylonas GP, 2020,

    Robotic surgery in cancer

    , BIOENGINEERING INNOVATIVE SOLUTIONS FOR CANCER, Editors: Ladame, Chang, Publisher: ACADEMIC PRESS LTD-ELSEVIER SCIENCE LTD, Pages: 245-269, ISBN: 978-0-12-813886-1
  • Conference paper
    Zhao M, Zhang H, Mylonas GP, Elson DSet al., 2020,

    Cable-driven parallel robot assisted confocal imaging of the larynx

    , Biophotonics Congress: Biomedical Optics 2020, Publisher: Optica Publishing Group, Pages: 1-2

    LaryngoTORS, a transoral laryngeal surgery robot, can manipulate instruments accurately. Confocal imaging has potentials in laryngeal cancer diagnosis but suffer from high scanning requirement. This work studies using LaryngoTORS to assist confocal imaging of larynx.

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