Cancer is one of the leading causes of death, making timely diagnosis and prognosis very important. Utilization of AI (artificial intelligence) enables providers to organize and process patient data in a way that can lead to better overall outcomes. This review paper aims to look at the varying uses of AI for diagnosis and prognosis and clinical utility. PubMed and EBSCO databases were utilized for finding publications from 1 January 2020 to 22 December 2023. Articles were collected using key search terms such as “artificial intelligence” and “machine learning.” Included in the collection were studies of the application of AI in determining cancer diagnosis and prognosis using multi-omics data, radiomics, pathomics, and clinical and laboratory data. The resulting 89 studies were categorized into eight sections based on the type of data utilized and then further subdivided into two subsections focusing on cancer diagnosis and prognosis, respectively. Eight studies integrated more than one form of omics, namely genomics, transcriptomics, epigenomics, and proteomics. Incorporating AI into cancer diagnosis and prognosis alongside omics and clinical data represents a significant advancement. Given the considerable potential of AI in this domain, ongoing prospective studies are essential to enhance algorithm interpretability and to ensure safe clinical integration.

Cancer is one of the leading causes of death, making timely diagnosis and prognosis very important. Utilization of AI (artificial intelligence) enables providers to organize and process patient data in a way that can lead to better overall outcomes. This review paper aims to look at the varying uses of AI for diagnosis and prognosis and clinical utility. PubMed and EBSCO databases were utilized for finding publications from January 1, 2013, to December 22, 2023. Articles were collected using key search terms such as “artificial intelligence” and “machine learning.” Included in the collection were studies of the application of AI in determining cancer diagnosis and prognosis using multi-omics data, radiomics, pathomics, clinical and laboratory data. The resulting 89 studies were categorized into eight sections based on the type of data utilized and then further subdivided into two subsections focusing on cancer diagnosis and prognosis, respectively. 8 studies integrated more than one form of omics, namely genomics, transcriptomics, epigenomics, and proteomics. Incorporating AI into cancer diagnosis and prognosis alongside omics and clinical data represents a significant advancement. Given the considerable potential of AI in this domain, ongoing prospective studies are essential to enhance algorithm interpretability and to ensure safe clinical integration.

Adhesive capsulitis (AC) and postoperative stiffness are characterized by fibrosis and contracture of the glenohumeral joint capsule, leading to progressive stiffness, pain, and limited range of motion (ROM). Diagnosis is confirmed clinically, with patients demonstrating reduced active and passive motion across multiple planes. While injections and physical therapy are commonly used treatments, no consensus exists regarding the most effective approach. This study aimed to assess patient-reported outcome measures (PROMs) and ROM for patients undergoing a large-volume hydrodilatation protocol under a suprascapular nerve block. Seventy-one patients diagnosed with AC or postoperative stiffness underwent ultrasound-guided large-volume glenohumeral joint hydrodilatation, which included an ultrasound-guided suprascapular nerve block at the suprascapular notch of the scapula prior to the procedure. The hydrodilatation injectate included 9 cc 1% lidocaine and 1 cc triamcinolone, followed by the injection of up to 110 cc sterile saline. ROM was measured immediately before and after the procedure, then at the final clinic follow-up. PROMs were assessed 6+ months following hydrodilatation using the Numeric Rating Scale for pain, the Shoulder Pain and Disability Index, and the Single Assessment Numeric Evaluation (SANE). Any further treatments that patients required were also recorded. Of the 71 patients, 47 were female and 24 were male. The mean age was 57 years old. Average pre-procedure forward flexion was 107°, which increased to 156° immediately post-procedure (<0.01) and remained at 153° at final follow-up (P < .01). External rotation pre-procedure ROM was 31°, increasing to 68° (P < .01) immediately post-procedure and 63° at follow-up (P < .01). Abduction demonstrated a pre-procedure ROM of 84°, an immediate post-procedure ROM of 120° (P < .01), and a final follow-up ROM of 101° (P < .01). PROM improvements were near established normal, with average Numeric Rating Scale was 1.9, Shoulder Pain and Disability Index 14.6, and SANE 85.3 compared to the contralateral shoulder SANE of 95. Large-volume hydrodilatation under suprascapular nerve block for AC resulted in significant improvements in ROM and satisfactory PROMs at a minimum 6 months follow-up.