Extent of use of artificial intelligence & machine learning protocols in cancer diagnosis: A scoping review.

Background & objectives: Artificial intelligence (AI) and machine learning (ML) have shown promising results in cancer diagnosis in validation tests involving retrospective patient databases. This study was aimed to explore the extent of actual use of AI/ML protocols for diagnosing cancer in prospective settings. Methods: PubMed was searched for studies reporting usage of AI/ML protocols for cancer diagnosis in prospective (clinical trial/real world) setting with the AI/ML diagnosis aiding clinical decision-making, from inception till May 17, 2021. Data pertaining to the cancer, patients and the AI/ML protocol were extracted. Comparison of AI/ML protocol diagnosis with human diagnosis was recorded. Through a post hoc analysis, data from studies describing validation of various AI/ML protocols were extracted. Results: Only 18/960 initial hits (1.88%) utilized AI/ML protocols for diagnostic decision-making. Most protocols used artificial neural network and deep learning. AI/ML protocols were utilized for cancer screening, pre-operative diagnosis and staging and intra-operative diagnosis of surgical specimens. The reference standard for 17/18 studies was histology. AI/ML protocols were used to diagnose cancers of the colorectum, skin, uterine cervix, oral cavity, ovaries, prostate, lungs and brain. AI/ML protocols were found to improve human diagnosis, and had either similar or better performance than the human diagnosis, especially made by the less experienced clinician. Validation of AI/ML protocols was described by 223 studies of which only four studies were from India. Also there was a huge variation in the number of items used for validation. Interpretation & conclusions: The findings of this review suggest that a meaningful translation from the validation of AI/ML protocols to their actual usage in cancer diagnosis is lacking. Development of regulatory framework specific for AI/ML usage in healthcare is essential.

Nature and mechanism of immune boosting by Ayurvedic medicine: A systematic review of randomized controlled trials.

BACKGROUND: Many Ayurvedic preparations are claimed to have immune-boosting properties, as suggested in various published randomized clinical trials (RCTs). AIM: To compile evidence on the nature and mechanism of immune system enhancement by Ayurvedic preparations in healthy and sick individuals. METHODS: After prospectively registering study protocol with PROSPERO, we searched PubMed, DOAJ, Google Scholar, three dedicated Ayurveda research portals, two specialty Ayurveda journals, and reference lists for relevant records published until February 6, 2021 using appropriate search strategies. Baseline features and data pertaining to the nature and mechanism of immune system function were extracted from all eligible records. Methodological quality was assessed using the Cochrane RoB-2 tool. RESULTS: Of 12554 articles screened, 19 studies reporting 20 RCTs (17 parallel group design, three crossover design) with 1661 unique patients were included; 11/19 studies had Indian first authors. Healthy population was included in nine studies, of which one study included pregnant women and two included pediatric population; remaining studies included patients with different health conditions, including one study with coronavirus disease 2019 patients. A total of 21 Ayurvedic interventions were studied, out of which five were composite mixtures. The predominant route of administration was oral; dose and frequency of administration of the intervention varied across the studies. The results reported with five RCTs exploring five Ayurvedic interventions were incomplete, ambiguous, or confusing. Of the remaining 16 interventions, indirect evidence of immune enhancement was reported with four interventions, while lack of the same was reported with two interventions. Enhancement of T helper cells and natural killer cells was reported with three and four interventions, respectively, while the pooled results did not clearly point toward enhancement of other components of the immune system, including cytotoxic T cells, B lymphocytes, immunoglobulins, cytokines, complement components, leucocyte counts, and other components. Nine of the 20 RCTs had a high risk of bias, and the remaining 11 RCTs had some concerns according to RoB-2. CONCLUSION: Various Ayurvedic preparations appear to enhance the immune system, particularly via enhancements in natural killer cells and T helper cells.

Importance of Evidence-Based Health Insurance Reimbursement and Health Technology Assessment for Achieving Universal Health Coverage and Improved Access to Health in India.

OBJECTIVE: To review the importance of evidence-based methods in health insurance reimbursement for achieving universal health coverage in India. METHODS: A narrative literature review was performed. RESULTS: The out-of-pocket (OOP) healthcare expenditure in India is among the highest in the world. This situation is despite the implementation of numerous government health schemes and the availability of a large number of health insurance programs, both public and private. Compromised quality of care in many public healthcare facilities is a major factor driving the average Indian citizen to increasingly depend upon private healthcare facilities, further escalating OOP spending. The low awareness and poor uptake of insurance policies among Indians is one of the biggest challenges in the implementation of universal health coverage (UHC) in India. The catastrophic burden of high OOP expenses on individual households could be reduced by taking steps to enhance health insurance uptake, which can be in turn achieved by strengthening the healthcare reimbursement system in India. CONCLUSIONS: The application of the principles of evidence-based healthcare for reimbursement requires the systematic assessment of all health technologies, which is already being done in developed countries. The enactment of health schemes such as Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana and setting up of Health Technology Assessment in India are steps toward reducing OOP expenditure and achieving UHC in India. We review the importance and challenges of evidence-based reimbursement and health technology assessment toward achieving UHC in India.