In the realm of pharmaceutical liability, failure to warn or to provide sufficient information such as adverse reaction or allergies of pharmaceutical products may cause manufacturers to be liable under the traditional common law of tort for the harm or death it causes. This article shows that manufacturers of prescribed pharmaceutical products may escape such liability if information and warnings have been conveyed to physicians; a learned intermediary between the manufacturers and the patients. The learned intermediary rule acts as a defence mechanism for manufacturers of pharmaceutical products as the physician is deemed as an intervening force that breaks the chain of causation in the law of negligence. Hence, the main focus of this article is to examine whether Malaysian courts would accept such a defence if invoked by the manufacturers. The objective of the article is to analyze and identify the learned intermediary between the manufacturer of a prescribed pharmaceutical products and patients under the relevant Malaysian statutes, particularly Poison Act 1952 and Medicines
Cervical cancer is known as a major health problem globally, with high mortality as well as incidence rates. Over the years, there have been significant advancements in cervical cancer detection techniques, leading to improved accuracy, sensitivity, and specificity. This article provides a chronological review of cervical cancer detection techniques, from the traditional Pap smear test to the latest computer-aided detection (CAD) systems. The traditional method for cervical cancer screening is the Pap smear test. It consists of examining cervical cells under a microscope for abnormalities. However, this method is subjective and may miss precancerous lesions, leading to false negatives and a delayed diagnosis. Therefore, a growing interest has been in shown developing CAD methods to enhance cervical cancer screening. However, the effectiveness and reliability of CAD systems are still being evaluated. A systematic review of the literature was performed using the Scopus database to identify relevant studies on cervical cancer detection techniques published between 1996 and 2022. The search terms used included “(cervix OR cervical) AND (cancer OR tumor) AND (detect* OR diagnosis)”. Studies were included if they reported on the development or evaluation of cervical cancer detection techniques, including traditional methods and CAD systems. The results of the review showed that CAD technology for cervical cancer detection has come a long way since it was introduced in the 1990s. Early CAD systems utilized image processing and pattern recognition techniques to analyze digital images of cervical cells, with limited success due to low sensitivity and specificity. In the early 2000s, machine learning (ML) algorithms were introduced to the CAD field for cervical cancer detection, allowing for more accurate and automated analysis of digital images of cervical cells. ML-based CAD systems have shown promise in several studies, with improved sensitivity and specificity reported compared to traditional screening methods. In summary, this chronological review of cervical cancer detection techniques highlights the significant advancements made in this field over the past few decades. ML-based CAD systems have shown promise for improving the accuracy and sensitivity of cervical cancer detection. The Hybrid Intelligent System for Cervical Cancer Diagnosis (HISCCD) and the Automated Cervical Screening System (ACSS) are two of the most promising CAD systems. Still, deeper validation and research are required before being broadly accepted. Continued innovation and collaboration in this field may help enhance cervical cancer detection as well as ultimately reduce the disease’s burden on women worldwide.
The COVID-19 vaccination program in Malaysia is an effort launched by the Malaysian government as a means of containing the spread of coronavirus disease 2019 (COVID-19) and ending the outbreak in Malaysia by developing herd immunity among its citizens and noncitizen. A major effort will be required from health agencies, non-governmental organizations, industries, national and also state governments. In some states, low vaccination rates have resulted in outbreaks of Covid-19, while also impeding the government's efforts to achieve its aim. The goal of this study is to establish the antecedents of Covid-19 vaccination acceptability in which to establish the data's reliability and validity, a two-stage pilot study was conducted. Several antecedents were identified and examined and analysed using SPSS software. Findings of study in first stage postulated the items were validated and the elimination of more than 20% items indicated that item validity had been violated. Meanwhile, the second pilot tests produced high internal consistency of above 0.7 of the minimal value for cronbach alpha after further improvement. In summary, this paper validated the measurement of research variables and not all items can be used in examining the vaccine readiness in Malaysia context of study. The actual data will use the item validation based on this pilot study.
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