Advertisement for orthosearch.org.uk
Results 1 - 20 of 58
Results per page:
Bone & Joint Research
Vol. 6, Issue 12 | Pages 665 - 666
1 Dec 2017
Hamilton DF Giesinger JM Giesinger K


The Bone & Joint Journal
Vol. 106-B, Issue 2 | Pages 108 - 110
1 Feb 2024
Haddad FS


The Bone & Joint Journal
Vol. 106-B, Issue 7 | Pages 642 - 645
1 Jul 2024
Harris IA Sidhu VS MacDessi SJ Solomon M Haddad FS


The Bone & Joint Journal
Vol. 106-B, Issue 2 | Pages 111 - 113
1 Feb 2024
Howard A Thomas GER Perry DC


The Bone & Joint Journal
Vol. 106-B, Issue 3 | Pages 224 - 226
1 Mar 2024
Ferguson D Perry DC


The Bone & Joint Journal
Vol. 104-B, Issue 12 | Pages 1281 - 1283
1 Dec 2022
Azizpour K Birch NC Peul WC


The Bone & Joint Journal
Vol. 105-B, Issue 6 | Pages 587 - 589
1 Jun 2023
Kunze KN Jang SJ Fullerton MA Vigdorchik JM Haddad FS

The OpenAI chatbot ChatGPT is an artificial intelligence (AI) application that uses state-of-the-art language processing AI. It can perform a vast number of tasks, from writing poetry and explaining complex quantum mechanics, to translating language and writing research articles with a human-like understanding and legitimacy. Since its initial release to the public in November 2022, ChatGPT has garnered considerable attention due to its ability to mimic the patterns of human language, and it has attracted billion-dollar investments from Microsoft and PricewaterhouseCoopers. The scope of ChatGPT and other large language models appears infinite, but there are several important limitations. This editorial provides an introduction to the basic functionality of ChatGPT and other large language models, their current applications and limitations, and the associated implications for clinical practice and research.

Cite this article: Bone Joint J 2023;105-B(6):587–589.


The Bone & Joint Journal
Vol. 106-B, Issue 4 | Pages 303 - 306
1 Apr 2024
Staats K Kayani B Haddad FS


The Bone & Joint Journal
Vol. 105-B, Issue 5 | Pages 467 - 470
1 May 2023
McBryde CW Prakash R Haddad FS


The Bone & Joint Journal
Vol. 97-B, Issue 7 | Pages 871 - 874
1 Jul 2015
Breakwell LM Cole AA Birch N Heywood C

The effective capture of outcome measures in the healthcare setting can be traced back to Florence Nightingale’s investigation of the in-patient mortality of soldiers wounded in the Crimean war in the 1850s. Only relatively recently has the formalised collection of outcomes data into Registries been recognised as valuable in itself. With the advent of surgeon league tables and a move towards value based health care, individuals are being driven to collect, store and interpret data. Following the success of the National Joint Registry, the British Association of Spine Surgeons instituted the British Spine Registry. Since its launch in 2012, over 650 users representing the whole surgical team have registered and during this time, more than 27 000 patients have been entered onto the database. There has been significant publicity regarding the collection of outcome measures after surgery, including patient-reported scores. Over 12 000 forms have been directly entered by patients themselves, with many more entered by the surgical teams. Questions abound: who should have access to the data produced by the Registry and how should they use it? How should the results be reported and in what forum?. Cite this article: Bone Joint J 2015;97-B:871–4


The Bone & Joint Journal
Vol. 106-B, Issue 6 | Pages 516 - 521
1 Jun 2024
Al-Hourani K Haddad FS


The Bone & Joint Journal
Vol. 96-B, Issue 7 | Pages 853 - 854
1 Jul 2014
Parsons N Griffin XL Stengel D Carey Smith R Perry DC Costa ML

The Bone & Joint Journal provides the latest evidence to guide the clinical practice of orthopaedic surgeons. The benefits of one intervention compared with another are presented using outcome measures; some may be specific to a limb or joint and some are more general health-related quality of life measures. Readers will be familiar with many of these outcome measures and will be able to judge the relative benefits of different interventions when measured using the same outcome tool; for example, different treatments for pain in the knee measured using a particular knee score. But, how should readers compare outcomes between different clinical areas using different outcome measures? This article explores the use of standardised effect sizes. Cite this article: Bone Joint J 2014;96-B:853–4


Bone & Joint Research
Vol. 11, Issue 1 | Pages 23 - 25
17 Jan 2022
Matar HE Platt SR Bloch BV Board TN Porter ML Cameron HU James PJ


Bone & Joint 360
Vol. 11, Issue 1 | Pages 3 - 4
1 Feb 2022
Ollivere B


The Bone & Joint Journal
Vol. 104-B, Issue 2 | Pages 189 - 192
1 Feb 2022
Scott CEH Clement ND Davis ET Haddad FS


Bone & Joint Research
Vol. 10, Issue 9 | Pages 591 - 593
7 Sep 2021
Thompson JW Simpson AHRW Haddad FS


The Bone & Joint Journal
Vol. 103-B, Issue 6 | Pages 1005 - 1006
1 Jun 2021
Haddad FS


Bone & Joint 360
Vol. 10, Issue 1 | Pages 3 - 3
1 Feb 2021
Ollivere B


The Bone & Joint Journal
Vol. 102-B, Issue 11 | Pages 1431 - 1434
1 Nov 2020
Trompeter AJ Furness H Kanakaris NK Costa ML


The Bone & Joint Journal
Vol. 102-B, Issue 6 | Pages 658 - 660
1 Jun 2020
Judge A Metcalfe D Whitehouse MR Parsons N Costa M