Deep Learning application in chiropractic-based treatment

Machine learning has attracted a lot of attention over the last few years. Deep neural networks are now the state of the art machine learning models across a variety of areas, from image analysis to natural language processing, and they are widely deployed in medical image processing technology, medical data analysis, medical diagnostics and healthcare in general. With scientific advancement and a continued effective use, medical imaging will continue to help with earlier detection of health issues, aid in easier treatment, and provide increased preventative care. 

Chiropractic is a type of Complementary and Alternative Medicine (CAM) therapy in which the hands are used to manipulate the spine or other parts of the body. Chiropractic may be used to treat conditions such as back pain, neck pain, headache, and hand or foot problems and to improve overall health  The theory is that proper alignment of the body's musculoskeletal structure, particularly the spine, will enable the body to heal itself without surgery or medication. A chiropractor first takes a medical history, performs a physical examination, and may use lab tests or diagnostic imaging to determine if treatment is appropriate. Spinal manipulation and chiropractic care are generally considered safe, effective treatments for acute low back pain, the type of sudden injury that results from moving furniture or getting tackled.

The idea of this study is to analyze and classify the patient’s cervical images so that the effectiveness of the chiropractic could be predicted. This method can be utilized to help physicians decide whether this method of treatment could help the patients which can result in saving time and costs.