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  1. Suresh Kumar R, Almansour AI, Arumugam N, Altaf M, Menéndez JC, Kumar RR, et al.
    Molecules, 2016 Jan 29;21(2):165.
    PMID: 26840282 DOI: 10.3390/molecules21020165
    The microwave-assisted three-component reactions of 3,5-bis(E)-arylmethylidene]tetrahydro-4(1H)-pyridinones, acenaphthenequinone and cyclic α-amino acids in an ionic liquid, 1-butyl-3-methylimidazolium bromide, occurred through a domino sequence affording structurally intriguing diazaheptacyclic cage-like compounds in excellent yields.
  2. Selvan S, Thangaraj SJJ, Samson Isaac J, Benil T, Muthulakshmi K, Almoallim HS, et al.
    Biomed Res Int, 2022;2022:2003184.
    PMID: 35958813 DOI: 10.1155/2022/2003184
    Prenatal heart disease, generally known as cardiac problems (CHDs), is a group of ailments that damage the heartbeat and has recently now become top deaths worldwide. It connects a plethora of cardiovascular diseases risks to the urgent in need of accurate, trustworthy, and effective approaches for early recognition. Data preprocessing is a common method for evaluating big quantities of information in the medical business. To help clinicians forecast heart problems, investigators utilize a range of data mining algorithms to examine enormous volumes of intricate medical information. The system is predicated on classification models such as NB, KNN, DT, and RF algorithms, so it includes a variety of cardiac disease-related variables. It takes do with an entire dataset from the medical research database of patients with heart disease. The set has 300 instances and 75 attributes. Considering their relevance in establishing the usefulness of alternate approaches, only 15 of the 75 criteria are examined. The purpose of this research is to predict whether or not a person will develop cardiovascular disease. According to the statistics, naïve Bayes classifier has the highest overall accuracy.
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