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Article ; Online: Light microscopic iris classification using ensemble multi-class support vector machine.

Rehman, Amjad

2021 Volume 84, Issue 5, Page(s) 982–991

Abstract: Similar to other biometric systems such as fingerprint, face, DNA, iris classification could assist law enforcement agencies in identifying humans. Iris classification technology helps law-enforcement agencies to recognize humans by matching their iris ... ...

Abstract	Similar to other biometric systems such as fingerprint, face, DNA, iris classification could assist law enforcement agencies in identifying humans. Iris classification technology helps law-enforcement agencies to recognize humans by matching their iris with iris data sets. However, iris classification is challenging in the real environment due to its invertible and complex texture variations in the human iris. Accordingly, this article presents an improved Oriented FAST and Rotated BRIEF with Bag-of-Words model to extract distinct and robust features from the iris image, followed by ensemble multi-class-SVM to classify iris. The proposed methodology consists of four main steps; first, iris image normalization and enhancement; second, localizing iris region; third, iris feature extraction; finally, iris classification using ensemble multi-class support vector machine. For preprocessing of input images, histogram equalization, Gaussian mask and median filters are applied. The proposed technique is tested on two benchmark databases, that is, CASIA-v1 and iris image database, and achieved higher accuracy than other existing techniques reported in state of the art.
MeSH term(s)	Algorithms ; Humans ; Iris/diagnostic imaging ; Microscopy ; Support Vector Machine
Language	English
Publishing date	2021-01-12
Publishing country	United States
Document type	Journal Article
ZDB-ID	1099714-3
ISSN	1097-0029 ; 1059-910X
ISSN (online)	1097-0029
ISSN	1059-910X
DOI	10.1002/jemt.23659
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Article ; Online: Orange Alert.

Rehman, Abdul

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine

2020 Volume 27, Issue 9, Page(s) 937

Language	English
Publishing date	2020-02-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	1329813-6
ISSN	1553-2712 ; 1069-6563
ISSN (online)	1553-2712
ISSN	1069-6563
DOI	10.1111/acem.13925
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Zs.A 4479: Show issues

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Book: Handbuch der homöopathischen Arzneibeziehungen

Rehman, Abdur

2007

Title translation	Encyclopedia of remedy relationships in homoeopathy
Author's details	Abdur Rehman
Keywords	Homöopathisches Arzneimittel ; Arzneimittelwechselwirkung
Subject	Arzneimittel ; Arzneimittelinterferenz ; Arzneimittelinteraktion ; Interaktion ; Medikamente ; Homöopathisches Präparat
Language	German
Size	XXVIII, 353 S.
Edition	3., überarb. Aufl.
Publisher	Haug
Publishing place	Stuttgart
Publishing country	Germany
Document type	Book
HBZ-ID	HT015132513
ISBN	978-3-8304-7258-2 ; 3-8304-7258-7
Database	Catalogue ZB MED Medicine, Health

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2007 A 3092	order for loan	Magazin

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Article ; Online: DEW: A wavelet approach of rare sound event detection.

Gul, Sania / Khan, Muhammad Salman / Ur-Rehman, Ata

PloS one

2024 Volume 19, Issue 3, Page(s) e0300444

Abstract: This paper presents a novel sound event detection (SED) system for rare events occurring in an open environment. Wavelet multiresolution analysis (MRA) is used to decompose the input audio clip of 30 seconds into five levels. Wavelet denoising is then ... ...

Abstract	This paper presents a novel sound event detection (SED) system for rare events occurring in an open environment. Wavelet multiresolution analysis (MRA) is used to decompose the input audio clip of 30 seconds into five levels. Wavelet denoising is then applied on the third and fifth levels of MRA to filter out the background. Significant transitions, which may represent the onset of a rare event, are then estimated in these two levels by combining the peak-finding algorithm with the K-medoids clustering algorithm. The small portions of one-second duration, called 'chunks' are cropped from the input audio signal corresponding to the estimated locations of the significant transitions. Features from these chunks are extracted by the wavelet scattering network (WSN) and are given as input to a support vector machine (SVM) classifier, which classifies them. The proposed SED framework produces an error rate comparable to the SED systems based on convolutional neural network (CNN) architecture. Also, the proposed algorithm is computationally efficient and lightweight as compared to deep learning models, as it has no learnable parameter. It requires only a single epoch of training, which is 5, 10, 200, and 600 times lesser than the models based on CNNs and deep neural networks (DNNs), CNN with long short-term memory (LSTM) network, convolutional recurrent neural network (CRNN), and CNN respectively. The proposed model neither requires concatenation with previous frames for anomaly detection nor any additional training data creation needed for other comparative deep learning models. It needs to check almost 360 times fewer chunks for the presence of rare events than the other baseline systems used for comparison in this paper. All these characteristics make the proposed system suitable for real-time applications on resource-limited devices.
MeSH term(s)	Neural Networks, Computer ; Algorithms ; Wavelet Analysis ; Memory ; Support Vector Machine
Language	English
Publishing date	2024-03-28
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0300444
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Optimised stacked machine learning algorithms for genomics and genetics disorder detection in the healthcare industry.

Rehman, Amjad / Mujahid, Muhammad / Saba, Tanzila / Jeon, Gwanggil

Functional & integrative genomics

2024 Volume 24, Issue 1, Page(s) 23

Abstract: With recent advances in precision medicine and healthcare computing, there is an enormous demand for developing machine learning algorithms in genomics to enhance the rapid analysis of disease disorders. Technological advancement in genomics and imaging ... ...

Abstract	With recent advances in precision medicine and healthcare computing, there is an enormous demand for developing machine learning algorithms in genomics to enhance the rapid analysis of disease disorders. Technological advancement in genomics and imaging provides clinicians with enormous amounts of data, but prediction is still mostly subjective, resulting in problematic medical treatment. Machine learning is being employed in several domains of the healthcare sector, encompassing clinical research, early disease identification, and medicinal innovation with a historical perspective. The main objective of this study is to detect patients who, based on several medical standards, are more susceptible to having a genetic disorder. A genetic disease prediction algorithm was employed, leveraging the patient's health history to evaluate the probability of diagnosing a genetic disorder. We developed a computationally efficient machine learning approach to predict the overall lifespan of patients with a genomics disorder and to classify and predict patients with a genetic disease. The SVM, RF, and ETC are stacked using two-layer meta-estimators to develop the proposed model. The first layer comprises all the baseline models employed to predict the outcomes based on the dataset. The second layer comprises a component known as a meta-classifier. Results from the experiment indicate that the model achieved an accuracy of 90.45% and a recall score of 90.19%. The area under the curve (AUC) for mitochondrial diseases is 98.1%; for multifactorial diseases, it is 97.5%; and for single-gene inheritance, it is 98.8%. The proposed approach presents a novel method for predicting patient prognosis in a manner that is unbiased, accurate, and comprehensive. The proposed approach outperforms human professionals using the current clinical standard for genetic disease classification in terms of identification accuracy. The implementation of stacked will significantly improve the field of biomedical research by improving the anticipation of genetic diseases.
MeSH term(s)	Humans ; Health Care Sector ; Machine Learning ; Algorithms ; Databases, Genetic ; Genomics
Language	English
Publishing date	2024-02-02
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2014670-X
ISSN	1438-7948 ; 1438-793X
ISSN (online)	1438-7948
ISSN	1438-793X
DOI	10.1007/s10142-024-01289-z
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Article ; Online: Aging and Adiposity-Focus on Biological Females at Midlife and Beyond.

Rehman, Amna / Lathief, Sanam / Charoenngam, Nipith / Pal, Lubna

International journal of molecular sciences

2024 Volume 25, Issue 5

Abstract: Menopause is a physiological phase of life of aging women, and more than 1 billion women worldwide will be in menopause by 2025. The processes of global senescence parallel stages of reproductive aging and occur alongside aging-related changes in the ... ...

Abstract	Menopause is a physiological phase of life of aging women, and more than 1 billion women worldwide will be in menopause by 2025. The processes of global senescence parallel stages of reproductive aging and occur alongside aging-related changes in the body. Alterations in the endocrine pathways accompany and often predate the physiologic changes of aging, and interactions of these processes are increasingly being recognized as contributory to the progression of senescence. Our goal for this review is to examine, in aging women, the complex interplay between the endocrinology of menopause transition and post-menopause, and the metabolic transition, the hallmark being an increasing tendency towards central adiposity that begins in tandem with reproductive aging and is often exacerbated post menopause. For the purpose of this review, our choice of the terms 'female' and 'woman' refer to genetic females.
MeSH term(s)	Female ; Humans ; Adiposity ; Aging/metabolism ; Menopause/physiology ; Postmenopause ; Reproduction ; Obesity
Language	English
Publishing date	2024-03-04
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2019364-6
ISSN	1422-0067 ; 1422-0067 ; 1661-6596
ISSN (online)	1422-0067
ISSN	1422-0067 ; 1661-6596
DOI	10.3390/ijms25052972
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Article: High prevalence of vitamin D deficiency in HIV-infected individuals in comparison with the general population across Punjab province, Pakistan.

Kanwal, Wajiha / Rehman, Abdul

Saudi journal of biological sciences

2022 Volume 30, Issue 1, Page(s) 103484

Abstract: The status of vitamin D in individuals infected with human immunodeficiency virus (HIV), particularly in naïve as well as treated patients, has never been reported in the Pakistani population. A cross-sectional study was performed to measure vitamin D in ...

Abstract	The status of vitamin D in individuals infected with human immunodeficiency virus (HIV), particularly in naïve as well as treated patients, has never been reported in the Pakistani population. A cross-sectional study was performed to measure vitamin D in individuals infected with HIV living in various districts of the Punjab, Pakistan. 1000 persons attending various treatment centers of the Punjab were screened for HIV, hepatitis B virus (HBV), hepatitis C virus (HCV), and Syphilis. Total 398 patients met inclusion criteria and vitamin D level was measured in respective cases by using enzyme-linked immunosorbent assay (ELISA) technique. 232 samples from the healthy population were also included in present research. Demographic history and clinical parameters regarding HIV disease were evaluated. Comparison of variables was done to find out the link between vitamin D levels and characteristics of HIV infected persons and comparison to that of healthy individuals was performed. Among 398 HIV patients vitamin D deficiency and insufficiency was found among 15 % and 39 % while majority of the control participants had sufficient levels of vitamin D (78 %). Most of the HIV infected individuals were males (68.6 %) and had age between 24 and 47 years (67.8 %). A significant relationship was found for vitamin D level, lifestyle and CD4 count among HIV + ve non acquired immunodeficiency syndrome (AIDS) subjects (95 % CI;
Language	English
Publishing date	2022-10-31
Publishing country	Saudi Arabia
Document type	Journal Article
ZDB-ID	2515206-3
ISSN	2213-7106 ; 1319-562X
ISSN (online)	2213-7106
ISSN	1319-562X
DOI	10.1016/j.sjbs.2022.103484
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Article: Outcome of paediatric lobectomy by thoracotomy - a single centre, six-year experience.

Sohail, Hamza / Rehman, Abdul

JPMA. The Journal of the Pakistan Medical Association

2022 Volume 72, Issue 5, Page(s) 947–949

Abstract: This short report highlights the patient outcome of lung resections for congenital and acquired lung lesions in children who presented to the Liaquat National Hospital, Karachi, from January 2013 to April 2019. Common indications were congenital ... ...

Abstract	This short report highlights the patient outcome of lung resections for congenital and acquired lung lesions in children who presented to the Liaquat National Hospital, Karachi, from January 2013 to April 2019. Common indications were congenital pulmonary airway malformation (CPAM), congenital lobar emphysema (CLE), and bronchiectasis. Two patients died whereas, 21 were discharged home. Lung resection can be performed safely in children. Early diagnosis and surgery may improve the outcome.
MeSH term(s)	Child ; Humans ; Infant ; Lung/abnormalities ; Pneumonectomy ; Pulmonary Emphysema/congenital ; Retrospective Studies ; Thoracotomy ; Treatment Outcome
Language	English
Publishing date	2022-06-18
Publishing country	Pakistan
Document type	Journal Article
ZDB-ID	603873-6
ISSN	0030-9982
ISSN	0030-9982
DOI	10.47391/JPMA.0429
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Book ; Online: Neural Computing for Online Arabic Handwriting Character Recognition using Hard Stroke Features Mining

Rehman, Amjad

2020

Abstract: Online Arabic cursive character recognition is still a big challenge due to the existing complexities including Arabic cursive script styles, writing speed, writer mood and so forth. Due to these unavoidable constraints, the accuracy of online Arabic ... ...

Abstract	Online Arabic cursive character recognition is still a big challenge due to the existing complexities including Arabic cursive script styles, writing speed, writer mood and so forth. Due to these unavoidable constraints, the accuracy of online Arabic character's recognition is still low and retain space for improvement. In this research, an enhanced method of detecting the desired critical points from vertical and horizontal direction-length of handwriting stroke features of online Arabic script recognition is proposed. Each extracted stroke feature divides every isolated character into some meaningful pattern known as tokens. A minimum feature set is extracted from these tokens for classification of characters using a multilayer perceptron with a back-propagation learning algorithm and modified sigmoid function-based activation function. In this work, two milestones are achieved; firstly, attain a fixed number of tokens, secondly, minimize the number of the most repetitive tokens. For experiments, handwritten Arabic characters are selected from the OHASD benchmark dataset to test and evaluate the proposed method. The proposed method achieves an average accuracy of 98.6% comparable in state of art character recognition techniques. Comment: 16 pages
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Computation and Language
Subject code	006
Publishing date	2020-05-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The sustainable use of diverse plants accustomed by different ethnic groups in Sibi District, Balochistan, Pakistan.

Maria, Bibi / Saeed, Shazia / Ahmed, Alia / Ahmed, Maria / Rehman, Abdul

PloS one

2024 Volume 19, Issue 2, Page(s) e0294989

Abstract: The present study was conducted to analyze the utilization of medicinal plants (traditional as well as cultivated) and there recipes accustomed by different ethnic groups of Sibi District (SD), Balochistan, Pakistan. The study was carried out between ... ...

Abstract	The present study was conducted to analyze the utilization of medicinal plants (traditional as well as cultivated) and there recipes accustomed by different ethnic groups of Sibi District (SD), Balochistan, Pakistan. The study was carried out between 2018 and 2021 by using semi-structured and open-ended questionnaire.. The randomly selected methods applied for this study were mainly based on household surveys walk through and interview with indigenous communityage 40 to 80, a total of 75 plants, belonging to 63 genera and distributed among 33 plant families were recorded. The dominant Plant families were the Fabaceae (12%) of all studied taxa, followed by the Amaranthaceae (7%), Asteraceae (6%), Cucurbitaceae, Solanaceae, Poaceae (4% each), Rhamnaceae and Zygophyllaceae (3%). Thirty traditional Food Recipes (TFR) and Traditional Medicinal Recipes (TMR) were novel being first time reported from SD., which are utilized by the local communities in their daily routine. These ethnic TFR and TMR have a tremendous role in preservation and sustainable use of traditional food habits and culture. It was also documented that along with cultivated, the wild edible and medicinal plant preparations play a significant role in in the economic potential and primary health care system of the local communities. The study recommends the specific measures, such as small industries, improved export means, tourism and educational activities, to protect the traditional knowledge and biocultural heritage of the region before its erosion.
MeSH term(s)	Humans ; Medicine, Traditional ; Pakistan ; Ethnicity ; Plants, Medicinal ; Surveys and Questionnaires ; Ethnobotany ; Phytotherapy
Language	English
Publishing date	2024-02-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0294989
Database	MEDical Literature Analysis and Retrieval System OnLINE

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