6 results on '"Muhammad Waqar Azeem"'
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2. Gender and Racial Disparities among US Psychiatry Residents: A Review of Trends
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Faisal Khosa, Sundas Saboor, Sadiq Naveed, Beenish Safdar, Muhammad Waqar Azeem, and Amna Mohyud Din Chaudhary
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Male ,medicine.medical_specialty ,media_common.quotation_subject ,Graduate medical education ,Ethnic group ,03 medical and health sciences ,Race (biology) ,0302 clinical medicine ,Ethnicity ,Humans ,Medicine ,030212 general & internal medicine ,Psychiatry ,Retrospective Studies ,Accreditation ,media_common ,African american ,business.industry ,Public health ,Racial Groups ,Hispanic or Latino ,United States ,030227 psychiatry ,Psychiatry and Mental health ,Pacific islanders ,Female ,business ,Diversity (politics) - Abstract
Diversity provides better patient outcomes, reduces physician burnout, and therefore lessens the burden of the healthcare system. In this study, we explore the gender and racial trends in the recruitment of medical graduates into US psychiatry residency programs. Retrospective data analysis was performed utilizing the data from the Accreditation Council for Graduate Medical Education (ACGME) Data's annual Resource Books from the year 2007 to 2018. Demographic data, including gender and race, were extracted for psychiatry residents. Gender was categorized as Male, Female, and Not Reported. Race/ethnicity was categorized as White (Non-Hispanic), Asian/Pacific Islander, Hispanic, Black/African-American (Non-Hispanic), Native American/Alaskan, Others (not in the aforementioned categories), and Unknown. Female psychiatry residents relatively decreased by 2.6% whereas male psychiatry residents relatively increased by 15.5% from 2007 to 2018. Between the years 2011 and 2018, there was a relative increase in African American/Black and Native American/Alaskan psychiatry residents by 5.5% and 1%, respectively, whereas the Asian/Pacific Islanders, White (Non-Hispanic), and Hispanic/Latino psychiatry residents relatively decreased by 5.1%, 2.3%, and 1.7%, respectively. Despite the overall increase of women and ethnic minorities in US medical schools, women and racial minorities remain significantly under-represented in psychiatry residency programs in the US.
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- 2021
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3. Geological mapping and neo-tectonics studies of the eocene limestone distributed over Mala Khel Anticline, Trans Indus ranges, North-West Himalayas, Pakistan
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Nazir-ur- Rehman, Sajjad Ahmad, Shah Faisal, Asghar Ali, Muhammad Waqar Azeem, null Afrasiab, Shuja Ullah, and Salik Javed
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General Earth and Planetary Sciences ,General Environmental Science - Published
- 2022
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4. The hidden crisis: COVID-19 and impact on mental health of medical students in Pakistan
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Irum Aamer, Ghulam Rasool, Imran Ijaz Haider, Ali Burhan Mustafa, Muhammad Waqar Azeem, Zahid Kamal, Afzal Javed, and Nazish Imran
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Psychiatry ,medicine.medical_specialty ,Research ,media_common.quotation_subject ,education ,RC435-571 ,Stigma (botany) ,COIVD-19 ,Response bias ,Medical students ,Mental health ,Patient Health Questionnaire ,Sadness ,Psychiatry and Mental health ,Psychiatric history ,medicine ,Anxiety ,Pakistan ,medicine.symptom ,Psychology ,Depression (differential diagnoses) ,media_common - Abstract
Background Medical students have faced an enormous disruption to their lives due to the COVID-19 pandemic. The study aimed to assess the impact of COVID-19 on medical student’s psychological well-being in Pakistan. Following ethical approval, an online survey developed in collaboration with World Psychiatric Association (WPA) was distributed among medical students of 5 Medical colleges in the Punjab province of Pakistan between August and September 2020. Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and Risk Assessment Suicidality Scale (RASS) were used to assess psychological well-being. Data was analyzed using SPSS 26.0. Results Eleven hundred medical students responded, 756 (69%) being females. More than 2/3rd admitted that their emotional state got worse in relation to appearance of anxiety, insecurity, and sadness, compared to before the outbreak of COVID-19. Prevalence of anxiety and depressive symptoms were 48.6% and 48.1%, respectively. Female medical students, pre-clinical students, and those with a previous psychiatric history reported experiencing more anxiety and depression symptoms (P value Conclusion Our findings underscore that the impact of COVID-19 on medical students has been significant; hence, it is crucial for medical colleges to employ strategies to maintain the student’s well-being with safeguards like reassurance, support, and confidential student-centered psychiatric services. The use of virtual platforms (websites, email) to educate and screen students by staff members can create a positive impact. The limitations of this study include cross-sectional design, the possibility of selective participation being web-based survey, response bias, and the possibility of reluctance of students to report mental health problems due to stigma.
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- 2021
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5. Multi-Region Risk-Sensitive Cognitive Ensembler for Accurate Detection of Attention-Deficit/Hyperactivity Disorder
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Vasily Sachnev, Narasimman Sundararajan, Sundaram Suresh, B. S. Mahanand, Muhammad Waqar Azeem, and Saras Saraswathi
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Computer science ,business.industry ,Cognitive Neuroscience ,Crossover ,Cognition ,Pattern recognition ,02 engineering and technology ,medicine.disease ,Computer Science Applications ,Multiclass classification ,03 medical and health sciences ,0302 clinical medicine ,Operator (computer programming) ,Hinge loss ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Attention deficit hyperactivity disorder ,020201 artificial intelligence & image processing ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,Classifier (UML) ,030217 neurology & neurosurgery ,Extreme learning machine - Abstract
In this paper, we present a multi-region ensemble classifier approach (MRECA) using a cognitive ensemble of classifiers for accurate identification of attention-deficit/hyperactivity disorder (ADHD) subjects. This approach is developed using the features extracted from the structural MRIs of three different developing brain regions, viz., the amygdala, caudate, and hippocampus. For this study, the structural magnetic resonance imaging (sMRI) data provided by the ADHD-200 consortium has been used to identify the following three classes of ADHD, viz., ADHD-combined, ADHD-inattentive, and the TDC (typically developing control). From the sMRIs of the amygdala, caudate, and hippocampus regions of the brain from the ADHD-200 data, multiple feature sets were obtained using a feature-selecting genetic algorithm (FSGA), in a wraparound approach using an extreme learning machine (ELM) basic classifier. An improved crossover operator for the FSGA has been developed for obtaining higher accuracies compared with other existing crossover operators. From the multiple feature sets and the corresponding ELM classifiers, a classifier-selecting genetic algorithm (CSGA) has been developed to identify the top performing feature sets and their ELM classifiers. These classifiers are then combined using a risk-sensitive hinge loss function to form a risk-sensitive cognitive ensemble classifier resulting in a simultaneous multiclass classification of ADHD with higher accuracies. Performance evaluation of the multi-region ensemble classifier is presented under the following three scenarios, viz., region-based individual (best) classifier, region-based ensemble classifier, and finally a multiple-region-based ensemble classifier. The study results clearly indicate that the proposed “multi-region ensemble classification approach” (MRECA) achieves a much higher classification accuracy of ADHD data (normally a difficult problem because of the variations in the data) compared with other existing methods.
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- 2019
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6. Genetics of structural and functional brain changes in autism spectrum disorder
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Puneet Bagga, Ravinder Reddy, Ajaz A. Bhat, Muhammad Waqar Azeem, Khalid A. Fakhro, Santosh K. Yadav, Michael P. Frenneaux, Sheema Hashem, Sabah Nisar, and Mohammad Haris
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Scientific community ,Autism Spectrum Disorder ,Imaging genetics ,Context (language use) ,Genomics ,Review Article ,Disease ,Neuropsychiatry ,Polymorphism, Single Nucleotide ,behavioral disciplines and activities ,lcsh:RC321-571 ,Cellular and Molecular Neuroscience ,Intervention (counseling) ,mental disorders ,medicine ,Humans ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Biological Psychiatry ,business.industry ,Brain ,medicine.disease ,Developmental disorder ,Psychiatry and Mental health ,Autism spectrum disorder ,business ,Neuroscience - Abstract
Autism spectrum disorder (ASD) is a neurological and developmental disorder characterized by social impairment and restricted interactive and communicative behaviors. It may occur as an isolated disorder or in the context of other neurological, psychiatric, developmental, and genetic disorders. Due to rapid developments in genomics and imaging technologies, imaging genetics studies of ASD have evolved in the last few years. Increased risk for ASD diagnosis is found to be related to many specific single-nucleotide polymorphisms, and the study of genetic mechanisms and noninvasive imaging has opened various approaches that can help diagnose ASD at the nascent level. Identifying risk genes related to structural and functional changes in the brain of ASD patients provide a better understanding of the disease’s neuropsychiatry and can help identify targets for therapeutic intervention that could be useful for the clinical management of ASD patients.
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- 2020
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