19 Harley St, London, W1G 9QJ, UK

A Pilot Study Implementing a Machine Learning Algorithm to Use Artificial Intelligence to Diagnose Spinal Conditions Research Article

The London Spine Unit : most advanced spinal hospital in UK

Published article

CONCLUSIONS: Software-predicted diagnoses based on the data from patients with spinal pain had an accuracy rate of 72%, suggesting promise for augmented decision making using artificial intelligence in this setting.
Lumbar Decompression Surgery Expert. Best Spinal Surgeon UK

Pain Physician. 2022 Mar;25(2):171-178.

ABSTRACT

BACKGROUND: Chronic spinal pain is the most prevalent chronic disease, with chronic persistent spinal pain lasting longer than one-year reported in 25% to 60% of the patients. Health care expenditures have been escalating and the financial impact on the US economy is growing. Among multiple modalities of treatments available, facet joint interventions and epidural interventions are the most common ones, in addition to surgical interventions and numerous other conservative modalities of treatments. Despite these increasing costs in the diagnosis and management, disability continues to increase. Consequently, algorithmic approaches have been described as providing a disciplined approach to the use of spinal interventional techniques in managing spinal pain. This approach includes evaluative, diagnostic, and therapeutic approaches, which avoids unnecessary care, as well as poorly documented practices. Recently, techniques involving artificial intelligence and machine learning have been demonstrated to contribute to the improved understanding, diagnosis, and management of both acute and chronic disease in line with well-designed algorithmic approach. The use of artificial intelligence and machine-learning techniques for the diagnosis of spinal pain has not been widely investigated or adopted.

OBJECTIVES: To evaluate whether it is possible to use artificial intelligence via machine learning algorithms to analyze specific data points and to predict the most likely diagnosis related to spinal pain.

STUDY DESIGN: This was a prospective, observational pilot study.

SETTING: A single pain management center in the United States.

METHODS: A total of 246 consecutive patients with spinal pain were enrolled. Patients were given an iPad to complete a Google form with 85 specific data points, including demographic information, type of pain, pain score, pain location, pain duration, and functional status scores. The data were then input into a decision tree machine learning software program that attempted to learn which data points were most likely to correspond to the practitioner-assigned diagnosis. These outcomes were then compared with the practitioner-assigned diagnosis in the chart.

RESULTS: The average age of the included patients was 57.4 years (range, 18-91 years). The majority of patients were women and the average pain history was approximately 2 years. The most common practitioner-assigned diagnoses included lumbar radiculopathy and lumbar facet disease/spondylosis. Comparison of the software-predicted diagnosis based on reported symptoms with practitioner-assigned diagnosis revealed that the software was accurate approximately 72% of the time.

LIMITATIONS: Additional studies are needed to expand the data set, confirm the predictive ability of the data set, and determine whether it is broadly applicable across pain practices.

CONCLUSIONS: Software-predicted diagnoses based on the data from patients with spinal pain had an accuracy rate of 72%, suggesting promise for augmented decision making using artificial intelligence in this setting.

PMID:35322974

The London Spine Unit : most advanced spinal hospital in UK

Read the original publication:

A Pilot Study Implementing a Machine Learning Algorithm to Use Artificial Intelligence to Diagnose Spinal Conditions

Related Posts

0/5 (0 Reviews)

Trusindex Reviews

London Spine Unit Harley Street Hospital

A Focus on High Quality Specialised Care

We are a specialist Private Hospital based on Harley Street, London UK The Harley Street Hospital, Day Surgery Hospital

We provide exclusive health services for individuals seeking Advanced medical, non-surgical or minimally invasive treatments. We are covered by All Insurance Companies apart from AXA PPP

Our Medical Director and Lead Spinal Surgeon Mr Mo Akmal MD is a world renowned Spine Specialist Consultant with over 20 years of experience. He and his team have developed revolutionary techniques to perform all types of Spinal Surgery as a Day Case procedure without traditional General Anaesthetic.

We are constantly improving our techniques for treatment and improving facilities for our patients.

Book your Appointment Now 
Check out our Reviews 
Check out our Patient Videos 
Check our Mr Akmal’s Profile

 

What our patients say ...

Pain Physician. 2022 Mar;25(2):171-178.ABSTRACTBACKGROUND: Chronic spinal pain is the most prevalent chronic disease, with chronic persistent spinal pain lasting longer than one-year reported in 25% to 60% of the patients. Health care expenditures have been escalating and the financial impact on the US economy is growing. Among multiple modalities of treatments available, facet joint interventions…
Lumbar slipped Disc

Revolutionary Keyhole surgical technique to vaporise bulging discs

Dr Mo Akmal Medical Director
Dr Mo Akmal MD - Lead Spinal Surgeon

Laser Disc Surgery can be performed under local anaesthetic at The Harley Street Hospital.

Initial Consultation

with Consultant Spine Surgeon
£ 250
  • No Waiting Times
  • Top NHS affiliated Consultant
  • Includes Clinical Review and Report
  • Multidisciplinary discussion
  • Review of Previous Scans and Reports

Follow up Consultation

any appointment after initial consultation
£ 180
  • Top NHS affiliated Consultant
  • Includes Clinical Review and Report
  • Multidisciplinary discussion

High Resolution MRI Scan

any Single Region (3.0 Tesla)
£ 600
  • No waiting times
  • Includes Full Radiologist Report
  • Open or Closed MRI scan types
  • Copy of Scan on CD

Website Offer

Pre-Booked Online
£1130
£ 800
  • Initial Consultation
  • MRI Scan (Single Region)
  • Follow Up consultation
  • Same Day One Stop Visit
  • Full Medical and MRI scan Report
  • Copy of scan on CD
Popular

If you have any emergency Doctor’s need, simply call our 24 hour emergency

Your personal case manager will ensure that you receive the best possible care.

Call Now 

+44 844 589 2020
+44 203 973 8810