USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPROACHES TO ENHANCE CANCER THERAPY AND DRUG DISCOVERY: A NARRATIVE REVIEW.

Background: This paper looks at how AI and machine learning have been applied over the last ten years to the development of anti-cancer drugs. By speeding up the synthesis of more desirable compounds and the identification of new ones, artificial intelligence (AI) has demonstrated substantial contributions to the research and therapy of anti-cancer therapies.

Methods: This work is a narrative review that examines numerous uses of AI-based techniques in the development of anti-cancer medications.

ArSa-Tweets: A novel Arabic sarcasm detection system based on deep learning model.

Sarcasm in Sentiment Analysis (SA) is important due to the sense of sarcasm in sentences that differs from their literal meaning. Analysis of Arabic sarcasm still has many challenges like implicit indirect idioms to express the opinion, and lack of Arabic sarcasm corpus. In this paper, we proposed a new detecting model for sarcasm in Arabic tweets called the ArSa-Tweet model.

Web-based pronunciation training and learning consonant clusters among EFL learners.

Arab learners of English often face challenges when it comes to correctly pronouncing English consonant clusters. To address these difficulties, technology-driven methods can be employed to enhance the acquisition of proper English consonant cluster pronunciation. This research endeavor aimed to assess the impact of web-based pronunciation training on the articulation of consonant clusters.

Coronary risk factor profiles according to different age categories in premature coronary artery disease patients who have undergone percutaneous coronary intervention.

Many studies have investigated the coronary risk factors (CRFs) among premature coronary artery disease (PCAD) patients. However, reports on the proportion and CRFs of PCAD according to different age cut-offs for PCAD is globally under-reported. This study aimed to determine the proportion of PCAD patients and analyse the significant CRFs according to different age cut-offs among percutaneous coronary intervention (PCI)-treated patients.

MRI Findings Reflecting Ongoing Cardiac Arrest While Being on an MRI Scanner.

Sudden cardiac arrest (SCA) is the abrupt loss of cardiac function that results in acute cardiovascular collapse and subsequent decreased or loss of various organ perfusion. Here, we present an interesting case of a 58-year-old man who developed abnormal brain MRI findings reflecting ongoing cardiac arrest due to pulseless electric activity (PEA) during an MRI scan. To our knowledge, this is the first case describing the MRI findings of ongoing cardiac arrest due to PEA.