جستجوی مقالات مرتبط با کلیدواژه « تشخیص » در نشریات گروه « پزشکی »

Nanorobots, also known as nanobots, are promising medical structures with significant potential for revolutionizing medical treatments and preventing their onset. Nanorobotics shows promise for diagnosing, treating, and regenerating age-related diseases. These tiny machines can repair cellular damage, deliver drugs, stimulate tissue regeneration, and monitor treatments. However, their application in controlling cellular aging is in its early stages, requiring more research to fully understand their potential and address safety concerns. Despite this, the benefits of nanorobots in age-related disease management justify further investigation. This narrative review article provides an overview of recent developments in nanorobotics, specifically focusing on its medical applications. PubMed and Google Scholar were utilized to conduct a comprehensive search using relevant keywords including "nanorobots", "cellular aging", "drug delivery systems", "cellular repair", "therapeutics", and "diagnosis". Only articles published between 2005-2023 were selected to support the arguments with up-to-date evidence. The extracted information includes nanorobot design, fabrication methods, applications, and key findings. A quality assessment was performed, and the data were categorized thematically to identify patterns and trends. The article concludes with an examination of the current state and future prospects of nanorobotics in different fields. Our research showed that nanorobots have significant potential in the diagnosis, treatment, and regenerative medicine of age-related diseases. They can detect and repair cellular damage caused by aging, targeting DNA damage and cellular protein misfolding. Nanorobots can also deliver drugs directly to affected areas, reducing side effects. Furthermore, they stimulate tissue regeneration and the growth of new blood vessels by delivering growth factors. Nanorobots can also monitor treatment effectiveness by measuring drug concentration in tumor cells. However, there are concerns about their safety in long-term use that require further research. Overall, nanorobots present an innovative approach to addressing cellular changes in aging, but more research is needed to understand their full potential and address safety concerns. The use of nanorobots in treating cellular aging has opened new possibilities in diagnosing and treating age-related diseases and it is a rapidly evolving field with the potential to revolutionize age-related disease treatment and improve the quality of life globally.

Viruses are sub-microscopic infectious agents that cause many diseases in humans, including several fatal infections that have emerged in the recent past. Rapid and accurate diagnosis of viral infections in the early stages is crucial in preventing the emergence of the pathogen. However, most of the currently available diagnostic methods are laborious, time-consuming, and less sensitive. On the other hand, the limited availability of antiviral treatments and the adverse effects associated with traditional antiviral drugs suggest the necessity of developing new therapeutic strategies to combat viral infections. In recent years, various types of nanomaterials have been investigated for the diagnosis and treatment of viral infections. In this review article, some of the nanotechnology-based approaches that have been developed for rapid and high-quality detection of viral infections, as well as antiviral therapeutic strategies related to nanomaterials, are also discussed with examples. Viral infections have emerged as a major threat to global health, especially in recent years. However, only a limited number of diagnostic tools and antiviral treatments are available to combat these viral infections. New approaches based on nanotechnology can provide a better platform for detecting viral infections in a short time with high sensitivity compared to existing viral detection methods. Also, nanomaterials may help overcome issues such as low solubility and bioavailability, rapid release, development of resistance, and adverse effects often associated with conventional antiviral therapies. Therefore, nanotechnology appears as a new and promising tool in the effective management of viral infections in future medicine.

Sarcoidosis is a granulomatous disorder characterized by non-caseating granulomas in multiple organs and an unknown cause. This chronic inflammatory disease is heterogeneous in terms of manifestations, duration, and severity. Although its aetiology is not well understood, there are indications of the genetic basis and the involvement of specific microorganisms and vitamin D in the development of this disease. Sarcoidosis can affect individuals of any age; however, it is more commonly observed in young adults and middle-aged subjects. The clinical course of the disease is unpredictable; nevertheless, in general, it can manifest as pulmonary, cardiac, cutaneous, ocular, skeletal-muscular, neurological, and renal involvement. Pulmonary involvement occurs in most patients and respiratory failure is the most common cause of death associated with sarcoidosis. Although numerous biomarkers have been evaluated in recent decades for patients with sarcoidosis, the diagnostic method is complex and no single diagnostic test can confirm the disease. Future research should focus on the combination of biomarkers and more refined imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). By utilizing these techniques and markers, it may be possible to design diagnostic and therapeutic approaches. Corticosteroids are considered the mainstay of treatment for most patients. Moreover, novel therapies, including the administration of rituximab and repository corticotropin injection (a combination of adrenocorticotropic hormone analogs and other pituitary peptides [RCI, Acthar® Gel]), have been reported to be effective in some cases.

Introduction:

Accurate documentation of medical records is one of the important issues during the process of diagnosis and treatment of the disease. It is very important in terms of treatment, legal, educational, financial and research. This study aimed to determine awareness of medical students about principles of medical records documentation.

This descriptive-analytical and cross-sectional study was conducted in 2022-2023 at Zahedan university of medical sciences. The research population included medical students in the preclinical, clinical, and residency levels. The sample size was 260 medical students and the sampling method was quota sampling. The data collection tool was a researcher-made questionnaire. The validity and reliability of questionnaire were confirmed. Descriptive statistics (frequency, percentage, mean, and standard deviation) and analytical tests (T-test and One-way ANOVA) were used to analysis the research data.

The average awareness score obtained by the research community was 64.92±14.02 out of 74. The highest and lowest average scores were respectively related to the principles about the time frame of completing the information and the general principles of documenting the medical record. The test of the relationship between the variables of the research showed that only the relationship between the two variables of awareness level and educational level of students was significant.

In this study, the level of students' awareness about the principles of documenting medical records was optimal. But by comparing the different results of this research with previous similar studies, it can be said that teaching the principles of documentation over time has had a positive effect on improving the level of students' awareness.

Breast cancer is the most common cancer in women that causes more deaths than other cancers. Thermography is one of the methods of breast cancer diagnosis. The most important challenge in early detection of these images can be human error or lack of access to a skilled person. The use of artificial intelligence methods in image processing can be effective in early detection and reduction of human error. The main aim of this research was to introduce hybrid networks for intelligent diagnosis of breast cancer from thermographic images.

The thermographic images used in this study were collected from the DMR-IR database. First, the main features of the images were extracted by deep convolutional network (CNN). Then, FCNNs and SVM algorithms were used to classify breast cancer from thermographic images.

The accuracy rate for CNN_FC and CNN-SVM algorithms was 94.2% and 0.95%, respectively. In addition, the reliability parameters for these classifiers were calculated as 92.1%, and 97.5%, and the sensitivity for each of these classifiers as 95.5%, and 94.1%, respectively.

The proposed model based on the deep hybrid network has good accuracy compared to similar algorithms; therefore, it can help doctors in the early diagnosis of breast cancer through thermographic images and minimize human error.

The genus mycobacterium comprises more than 160 species, some of which are pathogenic to humans. A variety of diseases, including pulmonary disease, skin and soft tissue infections, lymphadenitis, and disseminated disease, are caused by mycobacteria. Accurate detection of species is of great importance in the correct treatment of diseases caused by mycobacteria. The most commonly used methods for the diagnosis of mycobacteria include clinical symptoms and testing samples, microscopic methods, serology, radiology, biochemical tests, culture, nucleic acid amplification techniques (NAATs) including PCR, gene amplification and sequencing, etc. Here, we review recent advances in molecular tests for the detection of tuberculosis and other mycobacterial diseases, considering their sensitivity and specificity.

Oral cancer is a prevalent malignant tumor among head and neck cancers, and Oral squamous cell carcinoma (OSCC) accounts for 90% of oral cancers. Early diagnosis and treatment is the most important factor in reducing the mortality of OSCC, the purpose of this study is to investigate the level of awareness of final year dental students at Isfahan Azad University about the methods used to diagnose OSCC lesions.

In this cross-sectional descriptive study, which was conducted in the academic year of 2021-2022 among 82 final year students from the Faculty of Dentistry at Isfahan Azad University, a research questionnaire was distributed among the students. Data analysis was done in two descriptive and inferential sections. The collected data were analyzed using non-parametric Mann-Whitney test and Spearman correlation coefficient at the error level of 0.05% (p value < 0.05).

The findings of the current research indicate that 47.9% of female students and 52.1% of male students; 80.5% of students were single, 19.5% were married, 74.4% were native and 25.6% were non-native. The average knowledge score was above average (3.48 out of 6), and there were no significant differences in the average knowledge scores between male and female students, single and married, and native and non-native (p value > 0.05).

The results of the present study showed that the level of knowledge and awareness among final year dental students of Isfahan Islamic Azad University in relation to the diagnosis of OSCC lesions is average and far from the ideal level.

Considering the increasing and alarming trend of overweight and obesity as well as its related complications, in this study, a comprehensive clinical guide for the medical care of patients with obesity was written based on the clinical recommendations of the American Endocrinology Association and the American College of Endocrinology, and it has been adjusted as much as possible based on the conditions in Iran.

A complete search was performed in the available databases without any restrictions with a specific strategy. Using the opinions of experts in this field, the best clinical guidelines were selected and obesity clinical guidelines were written for Iranian adults. Recommendations were given based on a detailed review of available clinical evidence and considering objective factors.

A total of 1788 references were used and in response to 9 clinical questions, 123 recommendations, including 160 special statements, were provided to determine a comprehensive medical care program for obesity. In this article, we discuss the prevention, screening, diagnosis, benefits and goals of obesity treatment. Questions 6 to 9 regarding obesity treatment steps and its individualization will be published in the next part of the article.

The detailed evidence-based questions and recommendations outlined in this study identify clinical considerations that facilitate decision-making in obese patients from screening and diagnosis to goals of treatment.

Hypothyroidism is a common, important endocrine disorder. In this study, we aimed to evaluate family physicians' knowledge about hypothyroidism. 

 Thi s an alytical cross-sectional study assessed the knowledge knowledge of hypothyroidismin 180 family physicians working in two Shiraz urban health centers in 2021. A researcher-made questionnaire containing four areas, including screening, diagnosis, treatment, and referral, was used. The total score of the questionnaire was 22. Initially, the validity and reliability of the questionnaire were confirmed in a pilot study. 

150 out of 180 participants completed the questionnaire. The average score was 15.7±2 of the total 22 scores. The mean scores on screening, diagnosis, treatment, and referral subscales were 0.8±3.2, 0.8±2.3, 1.4±6.6, and 0.6±3.5, respe ctively. Less than 50% of the doctors answered five out of 22 questions correctly. The doctor's age had a significant negative relationship with the questionnaire score. 

Although family physicians' knowledge was acceptable in screening, diagnosis, and referral areas, their knowledge of treatment was not sufficient. Using evidence-based national clinical guidelines and updating them at specific intervals, focusing on the performance of family physicians, can be an effective way to improve the knowledge and performance of these doctors. Planning for targeted retraining is suggested as another way to improve performance.

An unexpected number of people are at risk of Alzheimer's disease. Therefore, efforts to find effective preventive measures require to be intensified.

To diagnose Alzheimer's disease through EEG signals using an artificial neural network, the first step involves pre-processing the recorded raw EEG data. This pre-processing includes the application of a 0.5 to 45 Hz bandpass filter to eliminate interference from the city's electrical signals. From the pre-processed data, the feature will be extracted. These features are related to time and frequency domains. Fourier transform, wavelet, first component analysis, nonlinear features of entropy, correlation dimension, and fractal dimension are among the suggested features. The extracted features will be evaluated by analysis of variance or t-test. The features that had the ability to separate different classes and have better statistical distribution in variance analysis or t-test are selected.

According to the capabilities of the artificial neural network in identifying different patterns and categorizing information that is set during a learning process, in this research, the artificial neural network will be used to determine the nonlinear mapping between EEG signals and the diagnosis of Alzheimer's disease. The database was divided into two categories: training and testing. In other words, the artificial neural network with the characteristics of the recorded signals as input and sick or healthy as the output of the neural network, and finally the the output of the trained artificial neural network is the diagnosis of sick or healthy data. In the final stage, the performance of the developed neural network will be evaluated and compared.

Utilizing both EEG signals and artificial neural networks could represent a novel method for the diagnosis of Alzheimer's Disease in its early stages.

Congenital hypothyroidism (CH) is one of the most preventable causes of mental retardation throughout the world. The aim of this study was to evaluate the sensitivity and specificity of filter paper in screening for congenital hypothyroidism and to determine an appropriate cut-off point for filter TSH for recalling screened neonates.

In this cross-sectional study (descriptive analytic), the records of 2739 neonates who had been recalled during the CH screening program in the east of Tehran, Iran (health care centers of the Iran University of Medical Sciences), from March 2011 to March 2015, were studied. According to the CH screening program in Iran, the TSH on filter paper>5 is the current cut-off point for recalling the neonates. The data was analyzed with SPSS software, version 21. The ROC curve was used to determine the TSH cut-off point and the sensitivity and specificity of the filter test. The relationship between the filter and serum TSH was also determined. The study was approved by the Ethics Committee of the Iran University of Medical Sciences.

The recall rate was 5.4%. The prevalence of hypothyroidism was 3/1000 neonates (164). The prevalence in males and females was 51.1% and 48.9%, respectively, with no significant difference. The number of recalled neonates diagnosed as patients with congenital hypothyroidism based on the filter TSH level was 5<TSH≤10(71), 10<TSH≤20(39), 20<TSH(54). There was no significant difference in seasonal prevalence of hypothyroidism or mean TSH level on filter paper among the four seasons. There was a moderately significant relationship between serum and filter paper TSH levels (r=0.379, P<0.05). Based on the ROC curve, the cut-off point for recall of 6.5 mIU/L with a sensitivity 77.5(0.771-0.777) and specificity          58%(0.575-0.585) and an area under the ROC curve of 0.74 was obtained.

Based on the findings of the study, considering the kits available in the country and their sensitivity and specificity, the importance of diagnosing infants with congenital hypothyroidism, and the lower cost of filter paper than missing a hypothyroid infant, the current cut-off point is acceptable. However, more studies are needed in different regions of Iran to obtain more accurate results.

In this study, we investigated the expression profile of this disease to identify new hub genes to help diagnose hepatocellular carcinoma (HCC).

Weighted gene co-expression network (WGCNA) analysis was used in this study to identify key modules and hub genes associated with HCC in the GSE176271 dataset. We also looked at the clinical significance of key genes and the biological pathways linked to them in external databases. We validated the identified hub genes using data from the GEPIA and XenaBrowser databases.

The Midnight blue module was found to be significantly related to the pathological stage (r = 0.94, P = 1e-11). Five hub genes (CLEC4M, CLEC4G, FCN2, OIT3, and ASPG) were associated with prognosis using DEG identification and WGCNA analysis. The three biological pathways associated with the Midnight blue module were copper ion detoxification, cell ion homeostasis, and complement activation, as well as the lectin pathway.

The current study's findings provide new and effective molecular targets for the detection of HCC, which can improve patients’ prognosis.

Osteoporosis is the most common metabolic bone disease. It is a chronic disease and a socio-economic threat. The aim of this study was to develop a clinical guideline for osteoporosis to integrate service delivery. This study was designed and conducted in two phases: comprehensive systematic review and expert panel method. First, a comprehensive search of sources was conducted in reliable databases. Then, in the expert panel phase, the clinical questions and recommendations were presented to members of the panel of experts. Finally, among various recommendations for a clinical question, the recommendation, which was approved by more than 70% of the panel of experts, was chosen as the final recommendation. By reviewing the valid guidelines of the world, five guidelines were selected according to the screening criteria of the study and entered into the study. After holding several sessions with the panel of experts and reviewing the recommendations in the initial version, 28 questions and 181 recommendations were extracted. After obtaining the opinions of professors from different disciplines, the final recommendations were reviewed in a meeting with clinical experts, and based on the submitted opinions, the final version of the guideline update, in the form of 34 questions and 111 recommendations in the field of bone health (four questions, 12 recommendations), diagnosis and Evaluation (six questions, 19 recommendations), treatment and rehabilitation (17 questions, 67 recommendations), and Sarcopenia (seven questions, 13 recommendations), were presented. Due to the emphasis on the need for accessing valid protocols to provide optimal and useful services and address the care gap has developed the Osteoporosis Clinical Guide.

Urticaria is a common and challenging skin disorder. Diagnosis and treatment of urticaria is not limited to the field of dermatology. General physicians, internal medicine specialists, allergologists and clinical immunologists are also commonly involved in the management of patients with urticaria.Iranian Society of Dermatology developed a clinical practice guideline concerning diagnosis and treatment of urticaria that was published in 2018. The current guideline is the result of scientific papers that got published from April 2018 to August 2022.

COVID-19 is caused by a virus known as SARS-COV-2 virus in the worldwide. The initial symptoms are similar to the common cold, but whatever has been going on since the first occurrence of the disease, the symptoms are different. The purpose of this paper is to familiarize yourself with this virus from the beginning to its uncertain end.

The present study is a narrative review based on the information collected in valid databases with keywords such as Corona, COVID-19, Pandemic, Diagnosis, Prevention, Treatment and Their English Equivalents. The timeframe for selecting articles was from 2019 to 2021.

COVID-19 is an emerging acute respiratory syndrome that is transmitted through the respiratory tract by droplets, respiratory secretions. Covid-19 latency is 1-14 days (often 3-7 days) and is contagious during the commune. At the time of relapse, different degrees of symptoms occur in patients according to the physiological conditions of the affected person and environmental conditions. Over time, the virus has suffered mutations and various strains such as delta and omicron have appeared. The use of masks, hand washing and social distancing are the most important preventive methods and so far no definitive treatment has been found for this disease, but fortunately, vaccines have been made for prevention. Discussion and

The disease caused by COVID-19 is completely unknown and a variety of species have emerged and have not yet been fully and accurately revealed to humans, so the more scientific knowledge in this field increases, the greater the possibility of better coping with these diseases.

Background & Aims:

 Early diagnosis of liver diseases has a significant effect on the prevention of its complications as well as control and treatment of the disease. “Machine learning” is one of the branches of artificial intelligence that has many applications in the field of medical diagnosis. This study aimed to provide a model with high accuracy and reliability for diagnosing liver diseases using machine learning methods that can help physicians in the early diagnosis and control of liver diseases.

Materials & Methods:

 This applied-developmental study used the dataset of 583 liver patients. In order to more accurately diagnose of the people with liver diseases, the results of the three classifiers including: Random Forest, Support Vector Machine, and Artificial Neural Network were combined using Dempster-Shafer theory. Weka data mining tool and Python programming language were used to implement the model. The k-fold cross-validation method was applied to evaluate efficiency of the model.

The results showed that accuracy, sensitivity, and specificity in the proposed model were 91.47%, 89.52%, and 93.03%, respectively, which had a better performance than similar studies.

The proposed model in the studied statistical population has a better performance in diagnosing liver diseases, and can help physicians in early diagnosis of the disease and appropriate treatment of it in the early stages of it and thus prevent development of the disease.

Infertility refers to the inability to achieve a pregnancy after one year of regular sexual intercourse, without the use of contraceptive methods, half of which is due to male factor. The couples with infertility suffers from emotional and psychological problems which affect the health of the family. MicroRNAs (miRNAs) play an essential role in the process of spermatogenesis and infertility. The study aims to investigate the role of peripheral blood miRNAs, as non-invasive biomarkers, for the diagnosis and prognosis of male infertility. Information sources or data: In this review study, related articles published in English or Persian from 2012 to 2022 were searched and evaluated based on inclusion and exclusion criteria independently by three researchers.

The search was conducted using the keywords: Male infertility, Diagnosis, Identification, miRNAs, Biomarkers, Non-invasive, Peripheral blood, Semen analysis, Testicular biopsy, and Treatment in both English and Persian in ScienceDirect, PubMed, Medline, Google Scholar, SID, and Magiran databases.

Of 114 found articles, 47 were finally selected for the review. Their results showed that the diagnosis of male infertility by semen analysis do not provide accurate results due to the lack of molecular investigation and invasive testicular biopsy. They suggested the use of peripheral blood miRNAs to screen male infertility.

Considering the importance of childbearing and the global need for new and efficient diagnostic tools, miRNAs can be used as non-invasive, specific, stable, reproducible, and available biomarkers for screening and diagnosis of male infertility. This is a promising and challenging issue and needs further investigations.