Reviewing the Impact of Medical Waste on the Environment and Methods of Disposal | Chapter 8 | Research Advances in Environment, Geography and Earth Science Vol. 6

Medical waste occupies an important part in environmental pollution, as it is considered one of the most dangerous pollutants of the environment and negatively affects human life and health due to the serious diseases it causes and spreads rapidly among people, becoming a major challenge facing elements of the contemporary environment in general and health institutions in particular. A person has the right to obtain the necessary health care, whether by providing the necessary medicine or whoever provides it. This service has known a great development throughout the ages until it reached its highest levels and is known today as these last medical services. Despite the advantages they provide for the benefit of human beings, especially since medical waste is not like all waste, but rather consists of toxic chemical and metallic substances, as it may also contain tools and sharp metals that are dangerous to the environment and living organisms. This study provides a review of the impact of medical waste on the environment and methods of disposal.

 

Author (s) Details

 

Yusra A. Radeef
Department of Biology, College of Science, Babylon University, Iraq.

 

Please see the book here:- https://doi.org/10.9734/bpi/raeges/v6/392

Using Machine Learning Algorithms for Cancer Image Dataset: A Predictive and Prescriptive Analysis | Chapter 3 | Research Updates in Mathematics and Computer Science Vol. 2

 This paper focuses on the problem of using machine learning techniques on cancer/tumor prediction. One of the biggest applications of big data and machine learning is in the field of medical domain. Consequently, a health care organization that uses the techniques of machine learning and big data to treat patients see fewer mishaps or gets enough time to deal with them in advance. Classification and prediction of the images are fairly easy task for humans, but it takes more effort for a machine to do the same. Machine learning helps to attain this goal. It automates the task of classifying a large collection of images into different classes by labelling the incoming data and recognizes patterns in it, which is subsequently translated into valuable insights. Furthermore, the prediction of Osteosarcoma case for one of the four classes of tumor namely Non tumor, Non-Viable tumor, viable tumor, Viable: Non-Viable tumor has to be done. The quantitative analysis is done using various machine learning libraries of python. The three classification algorithms used for image analysis are random forest, SVM, and logistic regression. The metrics used for performing perspective analysis are precision, recall and F1 Score. The domain of medical imaging helps providing important information on anatomy and organ function subsequently detecting disease states. Although the characteristics of medical data make its analysis a big challenge notwithstanding that machine learning techniques could make the task easier. The results show that the random forest algorithm has performed best amongst the three classification algorithms when given with less complicated scenario, with prediction accuracy, precision, recall and f1 score of 100%. But the performance of every classification algorithm degrades when provided with the cases of Osteosarcoma which has got more complicated scatter graph. However, the logistic regression retains its performance by predicting tumor cases with 99% accuracy. For future scope, various other machine learning algorithms can be applied to observe their performance on the same set of features extracted from the cancer image data set.

Author(s) Details:

Divya Chauhan,
Department of Computer Applications, Government College Rampur, Himachal Pradesh, India.

Kishori Lal Bansal,
Department of Computer Science, Himachal Pradesh University, Shimla, India.

Please see the link here: https://stm.bookpi.org/RUMCS-V2/article/view/13942

An Overview on Saudi Health Care System | Chapter 8 | Research Highlights in Disease and Health Research Vol. 8

 This review devote effort to something health care system in Saudi Arabia from accepted view and the challenges opposing the Saudi health management system. Healthcare services had happened one of the excellent priorities of the Saudi Arabian government. In allure attempt to improve health duties, the Saudi government has installed heavily in the health care area. By responding to the demands of allure citizens the Saudi health whole introduced various changes over the age to implement achievement. This leads to bettering of Saudi population health in the current decades. Mass gathering in scrupulous events face important community health challenges like the transmission of infectious afflictions, exacerbation of non-able to be contracted diseases, and disorders related to feeling change.With the ultimate aim of providing free and accessible healthcare services for each Saudi citizen and expatriate working in all sector, the Saudi Arabian administration has committed enormous money to enhancing health management.

Author(s) Details:

Abdulhameed G. Albeshr,
King Abdulaziz Medical City for National Guard, Riyadh, Saudi Arabia.

Yazeed A. Alhabdan,
King Abdulaziz Medical City for National Guard, Riyadh, Saudi Arabia.

Please see the link here: https://stm.bookpi.org/RHDHR-V8/article/view/10849

Design and Modelling of Implantable Cardioverter Defibrillator under Low Power High Speed Sub-threshold Operation | Chapter 3 | Technological Innovation in Engineering Research Vol. 5

As a result of significant technical advancements, researchers and scientists have produced designs that work in the subthreshold and near threshold zones. Design experts have recently been more interested in low power circuits as the need for low power consumption devices has increased. The process of subthreshold design has grown more sensitive to PVT changes due to the exponential relationship between current in the subthreshold region, supply voltage (Vgs), and threshold voltage (Vth). Low power electronics have drawn inspiration from subthreshold operation and its underlying principles. This research describes the functionality and performance of a source linked logic circuit's sub threshold design in both static and dynamic modes of operation, and its application as a 28nm implanted cardioverter defibrillator. The study's goals cover SRAM design as well as other techniques, including Schmitt trigger-based SRAM and Source linked SRAM operating in subthreshold designs.

Author (s) Details:

T. Vasudeva Reddy,
ECE Department, B. V. Raju Institute of Technology, Narsapur, Telangana, India.

B. Nareshkumar,
ECE Department, B. V. Raju Institute of Technology, Narsapur, Telangana, India.

R. Anirudh Reddy,
ECE Department, B. V. Raju Institute of Technology, Narsapur, Telangana, India.

P. Kavitha Reddy,
ECE Department, B. V. Raju Institute of Technology, Narsapur, Telangana, India.

Please see the link here: https://stm.bookpi.org/TIER-V5/article/view/7462

Determining the Intravenous Medication Administration Errors and Trying to Find Solutions | Chapter 3 | Technological Innovation in Pharmaceutical Research Vol. 7

 Intravenous errors are among the most common and common medical errors, but no direct causes have been identified. The most common expression of errors in hospitals is the theory of human error, which can endanger patients' lives. Medication errors, whether caused by negligence, omissions, or a lack of education and experience, remain errors and causes of harm to the patient. This research study aims to identify vein errors and try to find solutions to avoid those errors, with the study being conducted on a sample of Baghdad hospitals. Although intravenous errors are among the most common medical errors, no direct causes have been identified. The theory of human error is the most common expression of errors in hospitals, which can endanger patients' lives. Medication errors, whether caused by negligence, omissions, or a lack of education and experience, continue to be errors and causes of harm to patients. The study will be conducted on a sample of Baghdad hospitals to identify vein errors and try to find solutions to avoid those errors. There were a total of 99 cases during the study period. Among these mistakes are 52 incorrect medications (drug-drug interaction, drug-disease interaction, and not indicated medication), 42 incorrect doses, and 42 incorrect routes of administration. Conclusion: Intravenous errors can cause significant harm to patients and healthcare providers, so they must be addressed appropriately. Medication errors can occur for a variety of reasons, including health care providers' lack of experience and knowledge, inaccurate communications that do not explain the drug or the exact dose. The medication or dosage prescribing errors were collected, discussed, and clarified so that the risks associated with them could be observed so that health care providers and hospital specialists could be alerted, and the study could serve as a warning to health organizations.

Author (S) Details

Omar Abdulwahid Salih
Department of Clinical Pharmacy, Faculty of Pharmacy, Al-Rafidain University College, Baghdad, Iraq.

View Book :- https://stm.bookpi.org/TIPR-V7/article/view/1840