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In this paper, the weight and unit pruning strategy are used to reduce the complexity of the CNN model so that it can be used on small devices for the diagnosis of lumbar spondylolisthesis. Experimental results reveal that by removing 90% of network load, the unit pruning strategy outperforms weight pruning while achieving 94.12% accuracy. Thus, only 30% (around 850532 out of 3955102) and 10% (around 251512 out of 3955102) of the parameters from each layer contribute to the outcome during weight and neuron pruning, respectively. The proposed pruned model had achieved higher accuracy as compared to the prior model suggested for lumbar spondylolisthesis diagnosis.<\/jats:p>","DOI":"10.1155\/2022\/2722315","type":"journal-article","created":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T21:20:06Z","timestamp":1652217606000},"page":"1-10","source":"Crossref","is-referenced-by-count":11,"title":["Diagnosis of Lumbar Spondylolisthesis Using a Pruned CNN Model"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5380-8623","authenticated-orcid":true,"given":"Deepika","family":"Saravagi","sequence":"first","affiliation":[{"name":"Department of Computer Application, SAGE University, Indore 452012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0372-6128","authenticated-orcid":true,"given":"Shweta","family":"Agrawal","sequence":"additional","affiliation":[{"name":"IAC, SAGE University, Indore 452012, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9293-0285","authenticated-orcid":true,"given":"Manisha","family":"Saravagi","sequence":"additional","affiliation":[{"name":"Physiotherapy Department, Railway Hospital, Kota, Rajasthan 324002, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5068-2690","authenticated-orcid":true,"given":"Md Habibur","family":"Rahman","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Islamic University, Kushtia-7003, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"issue":"6","key":"1","first-page":"1450","article-title":"Classification and correlational analysis on lower spine parameters using data mining techniques","volume":"7","author":"R. 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