Motivation: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Objective: Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis. This novel study aims to evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment, and then compare it to the traditional or non-AI-based approaches. Methodology: PRISMA was used to select the best 200 studies for AI in healthcare with a primary focus on cost reduction, especially towards diagnosis and treatment. We defined the diagnosis and treatment architectures, investigated their characteristics, and categorized the roles that AI plays in the diagnostic and therapeutic paradigms. We experimented with various combinations of different assumptions by integrating AI and then comparing it against conventional costs. Lastly, we dwell on three powerful future concepts of AI, namely, pruning, bias, explainability, and regulatory approvals of AI systems. Conclusions: The model shows tremendous cost savings using AI tools in diagnosis and treatment. The economics of AI can be improved by incorporating pruning, reduction in AI bias, explainability, and regulatory approvals.

Background: The objective of this study was to report the use of multi-targeted polymerase chain reaction (PCR) in the diagnosis of presumed tubercular uveitis. Multi-targeted PCR using three targets specific for Mycobacterium tuberculosis, i.e., IS6110, MPB64, and protein b, was performed on intraocular fluid samples of 25 subjects. Nine had presumed tubercular uveitis, six had intraocular inflammation secondary to a nontubercular etiology (disease controls), and ten had no evidence of intraocular inflammation (normal controls). As described previously, response to antitubercular therapy was considered as the gold standard. Results: Multi-targeted PCR was positive in seven out of nine patients with presumed tubercular uveitis and negative in all normal and disease controls. The sensitivity and specificity were 77.77% and 100%, respectively. For the diagnosis of presumed tubercular uveitis, multi-targeted PCR had a positive predictive value of 100% and a negative predictive value of 88.88%. Conclusion: Multi-targeted PCR can be a valuable tool for diagnosing presumed tubercular uveitis.

Background: Hematological abnormalities are a common complication of HIV infection. These abnormalities increase as the disease advances. Bone marrow abnormalities occur in all stages of HIV infection. Methods: Two hundred HIV infected individual were screened for hematological abnormalities from March 2007–March 2008. Absolute CD4 cell count analysis was carried out by flowcytometry. Depending on the results of the primary screening further investigations were performed, like iron studies, hemolytic work up, PNH work up and bone marrow evaluation. Other investigations included coagulation profile, urine analysis, blood culture (bacterial, fungal, mycobacterial), serology for Epstein Barr virus (EBV), Cytomegalovirus (CMV), Hepatitis B and C, and Parvo B19 infection. Results: The most common hematological abnormality was anemia, seen in 65.5% (131/200) patients. Iron deficiency anemia was seen in 49.2% (/200) cases while anemia of chronic disease occurred in 50.7% (/200) cases. Bone marrow evaluation was carried out in 14 patients out of which staging marrow was performed in 2 cases of non-Hodgkin's lymphoma (NHL) and did not show any bone marrow infiltration. In remaining12 cases bone marrow was done for evaluation of pancytopenia. Among patients with pancytopenia 50% (6/12) showed granulomas (4 were positive for AFB, 2 were positive for fungal cryptococci), 25% (3/12) showed hemophagocytosis. There was a strong negative correlation between anemia and CD4 counts in this study. Thrombocytopenia was seen in 7% (14/200) cases and had no significant correlation with CD4 counts. No patient had absolute neutrophil count (ANC) < 800 cells/μL. No case of coagulation abnormalities was found. Conclusion: Anemia in HIV patients can be a good clinical indicator to predict and access the underlying immune status. Patients should be investigated for hematological manifestations and appropriate steps should be taken to identify and treat the reversible factors.