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The article presents the discussion on adopting Artificial Intelligence (AI) for resolving complex problems. Topics include AI establishing significant relationships within a data set being employed in various clinical situations for diagnosis, therapy and prognosis; and with the increasing societal burden of both communicable and non communicable diseases in the healthcare sector.

Introduction: Variability in the levels of these trace elements may reflect altered insulin metabolism and poor glycaemic control in the background of elevated oxidative stress. Mineral metabolism is another entity that may be disrupted by diabetes mellitus. Conversely, there are studies implicating early imbalances of trace elements in upsetting glucose homeostasis and insulin metabolism. Aim: To estimate and compare serum zinc, copper and magnesium in Type 2 Diabetes Mellitus (DM) patients with non diabetic controls and to correlate the serum zinc, copper and magnesium with Glycated Haemoglobin levels in Type 2 DM. Materials and Methods: This cross-sectional study was conducted at the Sapthagiri Institute of Medical Sciences and Research Center, Bengaluru, Karnataka, India. The study included 30 Type 2 DM patients and 30 healthy, age and gender matched controls without Type 2 DM. Their serum levels of zinc, copper and magnesium were measured and compared. Statistical Package for the Social Sciences (SPSS) version 16 software was used to perform the statistical analysis. The data obtained was subjected to descriptive statistical analysis. Results: Mean±SD of serum zinc in Type 2 DM and controls was 93.44±46.99 μg/dL and 121.74±37.15 μg/dL, respectively. Serum zinc was significantly decreased in Type 2 DM. However, there was no significant alteration with respect to serum copper and magnesium. Pearson’s correlation analysis showed that the association between HbA1c with zinc (r=0.069, p=0.718), copper (r= -0.094, p=0.622) and magnesium (r=0.116, p=0.543) was random. Conclusion: Zinc deficiency noticed in Type 2 DM patients may be due to increased excretion in urine. Zinc oral preparations are cheap and easily available. Considering these, it can be further explored if micronutrient supplementation would help to improve the glycaemic variability in Type 2 DM. [ABSTRACT FROM AUTHOR]

Aims: To estimate serum lipid profile in oral squamous cell carcinoma and correlate the risk factors and lipid profile with oral squamous cell carcinoma. Materials and Methods: Lipid profile was done in agriculturists/laborers in the age group of 30-70 years; 56 subjects (cases = 28, control = 28) were included. Study was carried out for a duration of four months; statistical analyses applied were mean, standard deviation, and independent 't' test. P < 0.05 was considered statistically significant. Results: Eleven cases had buccal mucosa cancer, nine had tongue carcinoma, and eight had gingivobuccal sulcus carcinoma. Lipid profile such as total cholesterol, triglycerides, LDL cholesterol, non-high-density lipoprotein (non-HDL) cholesterol, and very-low-density lipoprotein (VLDL) were marginally and slightly elevated in cases compared to controls. HDL was grossly decreased in cases compared to controls. Conclusions: There was a significant association between HDL and squamous cell carcinoma; maximum number of SCC had a history of smoking in the range of 10-19 years, irrespective of other lipid parameters, constrained to the fact that lipids are genetically determined, have geographical variation, and are highly skewed. [ABSTRACT FROM AUTHOR]