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Fulltext Ceph-X: development and evaluation of 2D cephalometric system

Mosleh MA, Baba MS, Malek S, Almaktari RA

BMC Bioinformatics, 2016 Dec 22;17(Suppl 19):499.
PMID: 28155649 DOI: 10.1186/s12859-016-1370-5

BACKGROUND: Cephalometric analysis and measurements of skull parameters using X-Ray images plays an important role in predicating and monitoring orthodontic treatment. Manual analysis and measurements of cephalometric is considered tedious, time consuming, and subjected to human errors. Several cephalometric systems have been developed to automate the cephalometric procedure; however, no clear insights have been reported about reliability, performance, and usability of those systems. This study utilizes some techniques to evaluate reliability, performance, and usability metric using SUS methods of the developed cephalometric system which has not been reported in previous studies.
METHODS: In this study a novel system named Ceph-X is developed to computerize the manual tasks of orthodontics during cephalometric measurements. Ceph-X is developed by using image processing techniques with three main models: enhancements X-ray image model, locating landmark model, and computation model. Ceph-X was then evaluated by using X-ray images of 30 subjects (male and female) obtained from University of Malaya hospital. Three orthodontics specialists were involved in the evaluation of accuracy to avoid intra examiner error, and performance for Ceph-X, and 20 orthodontics specialists were involved in the evaluation of the usability, and user satisfaction for Ceph-X by using the SUS approach.
RESULTS: Statistical analysis for the comparison between the manual and automatic cephalometric approaches showed that Ceph-X achieved a great accuracy approximately 96.6%, with an acceptable errors variation approximately less than 0.5 mm, and 1°. Results showed that Ceph-X increased the specialist performance, and minimized the processing time to obtain cephalometric measurements of human skull. Furthermore, SUS analysis approach showed that Ceph-X has an excellent usability user's feedback.
CONCLUSIONS: The Ceph-X has proved its reliability, performance, and usability to be used by orthodontists for the analysis, diagnosis, and treatment of cephalometric.
Fulltext Knowledge of Medical Students Towards the Re-emergence of Human Monkeypox Virus

Raman H, Jamil A, Rasheed A, Abdulrahman Jairoun A, Lua PL, Ibrahim UI, et al.

Cureus, 2023 Oct;15(10):e46761.
PMID: 37954738 DOI: 10.7759/cureus.46761

INTRODUCTION: Declaration of human monkeypox(HMPX) virus as Public Health Emergency of International Concern (PHEIC) by World Health Organisation (WHO) has raised concerns among the public andlack of knowledge is a prominent challenge in curbing this outbreak. Therefore, assessment ofknowledge level on this outbreak among the medical students is also necessary due to the fact that they are the future healthcare practitioners who will be directly involved in the disease management as well as a major source of knowledge dissemination to the public.
AIM: The main objective of this study is to assess the knowledge level of medical students at Universiti Sultan Zainal Abidin (UniSZA) regarding the emergence of HMPX. Additionally, the study aims to investigate potential associations between socio-demographic characteristics and knowledge levels, while also identifying factors that predict a high level of knowledge in this context..
METHODS: A descriptive cross-sectional study was conducted among UniSZA undergraduatemedical students from Year 1 to Year 5. A validated questionnaire comprising six socio-demographic variables and 27 knowledge items was shared online. Descriptive statistics, non-parametric tests and multivariate logistic regression were performed using SPSS software.
RESULTS: A total of 138 medical students out of 300 participated in this study. Overall, the average knowledge score was 73.95% ±4.43, which indicates that the medical students have moderate knowledge level. Nearly half of them had good knowledge level (n= 68; 49.3%), 43 of them had moderate knowledge level (31.2%), and 27 of them had poor knowledge level (19.6%). There was a significant association between knowledge level and two factors: receiving information on HMPX during their education and seniority (P-value < 0.01 and P-value < 0.05, respectively). Besides, received information on HMPX during their education was a significant predicting factor of good knowledge level (P-value = 0.002).
CONCLUSION: The knowledge level among the medical students was relatively inadequate.
Fulltext Privacy-Aware Collaborative Learning for Skin Cancer Prediction

Ain QU, Khan MA, Yaqoob MM, Khattak UF, Sajid Z, Khan MI, et al.

Diagnostics (Basel), 2023 Jul 04;13(13).
PMID: 37443658 DOI: 10.3390/diagnostics13132264

Cancer, including the highly dangerous melanoma, is marked by uncontrolled cell growth and the possibility of spreading to other parts of the body. However, the conventional approach to machine learning relies on centralized training data, posing challenges for data privacy in healthcare systems driven by artificial intelligence. The collection of data from diverse sensors leads to increased computing costs, while privacy restrictions make it challenging to employ traditional machine learning methods. Researchers are currently confronted with the formidable task of developing a skin cancer prediction technique that takes privacy concerns into account while simultaneously improving accuracy. In this work, we aimed to propose a decentralized privacy-aware learning mechanism to accurately predict melanoma skin cancer. In this research we analyzed federated learning from the skin cancer database. The results from the study showed that 92% accuracy was achieved by the proposed method, which was higher than baseline algorithms.
Fulltext YOLO and residual network for colorectal cancer cell detection and counting

Haq I, Mazhar T, Asif RN, Ghadi YY, Ullah N, Khan MA, et al.

Heliyon, 2024 Jan 30;10(2):e24403.
PMID: 38304780 DOI: 10.1016/j.heliyon.2024.e24403

The HT-29 cell line, derived from human colon cancer, is valuable for biological and cancer research applications. Early detection is crucial for improving the chances of survival, and researchers are introducing new techniques for accurate cancer diagnosis. This study introduces an efficient deep learning-based method for detecting and counting colorectal cancer cells (HT-29). The colorectal cancer cell line was procured from a company. Further, the cancer cells were cultured, and a transwell experiment was conducted in the lab to collect the dataset of colorectal cancer cell images via fluorescence microscopy. Of the 566 images, 80 % were allocated to the training set, and the remaining 20 % were assigned to the testing set. The HT-29 cell detection and counting in medical images is performed by integrating YOLOv2, ResNet-50, and ResNet-18 architectures. The accuracy achieved by ResNet-18 is 98.70 % and ResNet-50 is 96.66 %. The study achieves its primary objective by focusing on detecting and quantifying congested and overlapping colorectal cancer cells within the images. This innovative work constitutes a significant development in overlapping cancer cell detection and counting, paving the way for novel advancements and opening new avenues for research and clinical applications. Researchers can extend the study by exploring variations in ResNet and YOLO architectures to optimize object detection performance. Further investigation into real-time deployment strategies will enhance the practical applicability of these models.
Fulltext DenseHillNet: a lightweight CNN for accurate classification of natural images

Saqib SM, Zubair Asghar M, Iqbal M, Al-Rasheed A, Amir Khan M, Ghadi Y, et al.

PeerJ Comput Sci, 2024;10:e1995.
PMID: 38686004 DOI: 10.7717/peerj-cs.1995

The detection of natural images, such as glaciers and mountains, holds practical applications in transportation automation and outdoor activities. Convolutional neural networks (CNNs) have been widely employed for image recognition and classification tasks. While previous studies have focused on fruits, land sliding, and medical images, there is a need for further research on the detection of natural images, particularly glaciers and mountains. To address the limitations of traditional CNNs, such as vanishing gradients and the need for many layers, the proposed work introduces a novel model called DenseHillNet. The model utilizes a DenseHillNet architecture, a type of CNN with densely connected layers, to accurately classify images as glaciers or mountains. The model contributes to the development of automation technologies in transportation and outdoor activities. The dataset used in this study comprises 3,096 images of each of the "glacier" and "mountain" categories. Rigorous methodology was employed for dataset preparation and model training, ensuring the validity of the results. A comparison with a previous work revealed that the proposed DenseHillNet model, trained on both glacier and mountain images, achieved higher accuracy (86%) compared to a CNN model that only utilized glacier images (72%). Researchers and graduate students are the audience of our article.
Fulltext Health-related quality of life among people with diabetes: A cross-sectional study in Hail region, Saudi Arabia

Alshammari F, Ansari M, Khan KU, Neupane D, Hussain A, Anwar S, et al.

PLoS One, 2024;19(5):e0299995.
PMID: 38713663 DOI: 10.1371/journal.pone.0299995

BACKGROUND: Diabetes Mellitus is a serious and expanding health problem, together with the issues of health- related quality of life (HRQoL). This further puts pressure on the government to allocate more funds for public healthcare.
OBJECTIVES: This study was devised to evaluate the health-related quality of life of people living with diabetes in Hail region of Saudi Arabia.
METHODS: This cross-sectional research was carried out at eight locations in the Hail region of Saudi Arabia between 21st March-20th May 2022 using the adapted version of the Euro QoL-5 dimension (EQ-5D-3L) questionnaire. A multistage random sample approach was used to choose the diabetes clinics, and data collectors approached the participants in the waiting areas to collect the information. The data were analyzed using logistic regression analysis, Mann-Whitney test, and Kruskal-Wallis tests in IBM SPSS statistics 21.0.
RESULTS: The mean HRQoL score was 0.71±0.21 with a visual analog score of 68.4±16.2. Despite having much higher levels of quality of life in terms of self-care (85.8%), regular activity (73.8%) and anxiety (71.8%), nearly one half of the people reported moderate pain or discomfort, and more than one third reported having moderate mobility issues. In general, the quality of life for women was poorer than for men. Individuals with diabetes who were unmarried, young, educated, financially secure, and taking only oral medication had much improved HRQoL. The Euro QoL of people with diabetes patients were significantly influenced by gender, marital status, age, education, employment and treatment modality (p-values < 0.05), whereas only treatment modality had a significant impact on the patients' visual analogue measures (p-values < 0.05).
CONCLUSIONS: The HRQoL of people with diabetes in Hail region was moderate in general, with pain and mobility issues being particularly prevalent. Gender, marital status, age, education, employment and type of medication therapy are significant predictors of HRQoL of patients with diabetes. Hence, planning and programs to enhance the HRQoL of people with diabetes, especially women is recommended.
Fulltext Factors Associated with Self-Medication during the COVID-19 Pandemic: A Cross-Sectional Study in Pakistan

Chaudhry B, Azhar S, Jamshed S, Ahmed J, Khan LU, Saeed Z, et al.

Trop Med Infect Dis, 2022 Oct 25;7(11).
PMID: 36355873 DOI: 10.3390/tropicalmed7110330

Self-medication (SM) is characterized by the procurement and use of medicines by bypassing primary healthcare services and without consulting a physician, usually to manage acute symptoms of self-diagnosed illnesses. Due to the limited availability of primary healthcare services and the anxiety associated with the COVID-19 pandemic, the compulsion to SM by the public has increased considerably. The study aimed to assess the characteristics, practices, and associated factors of SM by the public during the COVID-19 pandemic in Sargodha, Pakistan. χ2-tests and univariable analyses were conducted to explore the identification of characteristics and the potential contributing factors for SM during COVID-19, while multivariable logistic regression models were run to study the effect of variables that maintained a significant association. The study was performed during July−September 2021, with n = 460 questionnaires returned overall (response rate: 99.5%). The majority of respondents were males (58.7%, n = 270) who live in the periphery of the town (63.9%, n = 294), and most of the respondents belonged to the age group of 18−28 years (73.3%, n = 339). A large number, 46.1% (n = 212), of the participants were tested for COVID-19 during the pandemic, and among them, 34.3% (n = 158) practiced SM during the pandemic; the most common source of obtaining medicines was requesting them directly from a pharmacy (25.0%; n = 127). The chances of practicing SM for medical health professionals were 1.482 (p-value = 0.046) times greater than for non-medical health personnel. The likelihood of practicing SM in participants whose COVID-19 test was positive was 7.688 (p-value < 0.001) times more than who did not test for COVID-19. Allopathic medicines, acetaminophen (23.6%), azithromycin (14,9%), and cough syrups (13%), and over the counter (OTC) pharmaceuticals, vitamin oral supplements, such as Vitamin C (39.1%), folic acid (23.5%), and calcium (22.6%), were the most commonly consumed medicines and supplements, respectively; being a healthcare professional or having a COVID-test prior showed a significant association with the usage of Vitamin C (p < 0.05 in all cases). Respondents who mentioned unavailability of the physician and difficulty in travelling/reaching healthcare professionals were found 2.062-times (p-value = 0.004) and 1.862-times (p-value = 0.021) more likely to practice SM, respectively; SM due to fear of COVID was more common in individuals who had received COVID-tests prior (p = 0.004). Practices of SM were observed at alarming levels among our participants. Consciousness and understanding about the possible adverse effects of SM must be established and validated on a continuous level; in addition, on a commercial level, collaboration from pharmacists not to sell products (especially prescription-only medicines) without a certified prescription must be developed and implemented.
Fulltext Genome-Wide Association Analysis of Young-Onset Stroke Identifies a Locus on Chromosome 10q25 Near HABP2

Cheng YC, Stanne TM, Giese AK, Ho WK, Traylor M, Amouyel P, et al.

Stroke, 2016 Feb;47(2):307-16.
PMID: 26732560 DOI: 10.1161/STROKEAHA.115.011328

BACKGROUND AND PURPOSE: Although a genetic contribution to ischemic stroke is well recognized, only a handful of stroke loci have been identified by large-scale genetic association studies to date. Hypothesizing that genetic effects might be stronger for early- versus late-onset stroke, we conducted a 2-stage meta-analysis of genome-wide association studies, focusing on stroke cases with an age of onset <60 years.
METHODS: The discovery stage of our genome-wide association studies included 4505 cases and 21 968 controls of European, South-Asian, and African ancestry, drawn from 6 studies. In Stage 2, we selected the lead genetic variants at loci with association P<5×10(-6) and performed in silico association analyses in an independent sample of ≤1003 cases and 7745 controls.
RESULTS: One stroke susceptibility locus at 10q25 reached genome-wide significance in the combined analysis of all samples from the discovery and follow-up stages (rs11196288; odds ratio =1.41; P=9.5×10(-9)). The associated locus is in an intergenic region between TCF7L2 and HABP2. In a further analysis in an independent sample, we found that 2 single nucleotide polymorphisms in high linkage disequilibrium with rs11196288 were significantly associated with total plasma factor VII-activating protease levels, a product of HABP2.
CONCLUSIONS: HABP2, which encodes an extracellular serine protease involved in coagulation, fibrinolysis, and inflammatory pathways, may be a genetic susceptibility locus for early-onset stroke.
Fulltext Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Howson JMM, Zhao W, Barnes DR, Ho WK, Young R, Paul DS, et al.

Nat Genet, 2017 Jul;49(7):1113-1119.
PMID: 28530674 DOI: 10.1038/ng.3874

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10-8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.