3D Convolutional Neural Network Framework with Deep Learning for Nuclear Medicine.

Though artificial intelligence (AI) has been used in nuclear medicine for more than 50 years, more progress has been made in deep learning (DL) and machine learning (ML), which have driven the development of new AI abilities in the field. ANNs are used in both deep learning and machine learning in nuclear medicine. Alternatively, if 3D convolutional neural network (CNN) is used, the inputs may be the actual images that are being analyzed, rather than a set of inputs. In nuclear medicine, artificial intelligence reimagines and reengineers the field's therapeutic and scientific capabilities. Understanding the concepts of 3D CNN and U-Net in the context of nuclear medicine provides for a deeper engagement with clinical and research applications, as well as the ability to troubleshoot problems when they emerge. Business analytics, risk assessment, quality assurance, and basic classifications are all examples of simple ML applications. General nuclear medicine, SPECT, PET, MRI, and CT may benefit from more advanced DL applications for classification, detection, localization, segmentation, quantification, and radiomic feature extraction utilizing 3D CNNs. An ANN may be used to analyze a small dataset at the same time as traditional statistical methods, as well as bigger datasets. Nuclear medicine's clinical and research practices have been largely unaffected by the introduction of artificial intelligence (AI). Clinical and research landscapes have been fundamentally altered by the advent of 3D CNN and U-Net applications. Nuclear medicine professionals must now have at least an elementary understanding of AI principles such as neural networks (ANNs) and convolutional neural networks (CNNs).

Design, Synthesis, Docking and Biological Evaluation of Novel 4-hydroxy Coumarin Derivatives.

BACKGROUND: Hospital-acquired (HA) infections are caused due to E. coli, which is resistant to multiple drugs particularly to fluoroquinolone class of drugs. Urinary tract infections (UTI) affects people in the community and hospitals. 150 million people per annum are suffering from UTI worldwide. METHODS: In this present study, we designed 36 novel coumarin derivatives, also we predicted pharmacokinetic and toxicity parameters. Docking studies were also carried out and all the compounds were evaluated for antibacterial activity against resistant quinolone E. coli strain ATCC 25922. It was interesting to note that the introduction of electron-withdrawing group on the aromatic ring resulted in compounds with an increased antibacterial activity, which is observed in compound 6 (with 4-nitro substitution), compound 23 (chloro) and compound 30 (chloro, nitro). RESULTS: From the MIC results, it was observed that compounds 6, 23 and 30 showed higher activity with 0.5µg/ml, 0. 12 µg/ml, 0.5 µg/ml respectively. Docking studies were performed with the active site of DNA gyrase (PDB ID: 4CKK). The maximum binding energy was found to be -10.7 Kcal/mol. CONCLUSION: From the study, it was found that 3 compounds were potentially active against quinolone- resistant E. coli strains. This study can further be extended for in vivo evaluation.

A Comprehensive Review on DNA Gyrase Inhibitors.

The newly emerging infectious organisms, the global crisis in antibiotic resistance, and the threat of bioterrorism create an urgent need to discover novel antimicrobial agents. In order to develop novel antimicrobial agents, the mechanism of infectious disease must be better understood. DNA Gyrase is a bacterial enzyme that plays an important role in the replication of DNA and transcription process. It is not present in higher eukaryotes making it a perfect target for developing new antibacterial agents. This review describes the role of DNA gyrase inhibitors in preventing various diseases. In this review, we outline the synthesis and pharmacological action of various novel DNA gyrase inhibitors. DNA gyrase inhibitors were used to treat tuberculosis, bacterial, fungal infections and malaria. DNA gyrase inhibitors mainly act by preventing the supercoiling of DNA strands..

Accurate Approach Towards Efficiency of Searching Agents in Digital Libraries Using Keywords.

The age of information has done it simple for storing huge amount of data. In actual fact, a considerable segment of existing information is accumulated in the text databases that have huge set of documents from different sources like research articles, news articles, books, e-mail messages, web pages and digital libraries. In many text databases, stored data are in the semi-structured format in that they are neither entirely structured nor entirely unstructured. IR (Information Retrieval) field has been growing in parallel using database systems for several years. Contrasting to the databases system fields that have concentrated mainly on transaction and query processing of the structured data, IR is concerned with firm and retrieval of data from a huge quantity of text-oriented documents. Thus, IR tackles with unstructured and/or semi-structured databases. Information security requirements within a firm have experience major variations in the past some decades. By the establishment of computer, the necessary for automated equipment for securing files as well as other information that stored on the computer turned into evident. This is particularly in case of shared information resources via public network. This is the origin for having a secure computer system / the need for computer security. Computer Security can be achieved by Intrusion Detection Systems. In this paper, we address these issues by applying Similarity Search in two diversified fields: Digital Libraries and Computer Security. The paper discusses a fast and efficient similarity search technique for approximate retrieval of books metadata in Digital Libraries. In DLI the books retrieval takes place just by using metadata such as title, year, edition, author, publishing of a book. Though, if metadata is missing, incorrect or unfinished, then it creates the library retrieval system inefficient, incorrect leads too much confusion to the user. In this context even if the query from the user matches partially or fully with a stored pattern, the information related to that be retrieved. The paper talks about a method that functions rapid and effective, language independent, and flexible library retrieval system signature based similarity search. This system is able to retrieve not only the metadata that exactly matches the query but also fairly accurate identical because of missing words, jumbled words and spell mistakes. Fundamentally, signature file approach is used here. A signature file approach looks like the most capable for huge database as it has superior text retrieval features and requires little storage overhead.