International Journal of Current Research and Review
ISSN: 2231-2196 (Print)ISSN: 0975-5241 (Online)
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IJCRR - Vol 13 Issue 13, July, 2021

Pages: 70-73

Date of Publication: 05-Jul-2021


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Application of Machine Learning for Improving Early Cancer Diagnosis

Author: Jayasri Kotti

Category: Healthcare

Abstract:Across the world, cancer becomes a catastrophe for a human being who is suffering from it. Cancer can be diagnosed at a premature stage to overcome the consequences at a later stage and the possibility of endurance considerably, as it can support appropriate medical action to patients. One of the frequently used innovative technologies for the diagnosis and detection of cancer is Machine learning (ML). In recent times ML has been used for the prediction and prognosis of cancer. Machine learning enables the creation of algorithms that can learn and make predictions. Various Machine Learning techniques can build a model to diagnose cancer based on finding accuracy level. It is possible for early detection of cancer through machine learning where we train the machine with previous data. This paper aims to predict cancer type based on symptoms given by the user. Here we adopted a supervised learning algorithm and then use the Logistic Regression based on accuracy and recall score i.e., the algorithm which gives high accuracy level and recall score. The proposed System executes with good performance as it generates accurate results.

Keywords: Machine Learning (ML), Data sets, Symptoms, Cancer, Logistic Regression, Supervised Learning

Full Text:

 Introduction

Constant growth associated with cancer research has been achieved in the past few decades.  For screening in the premature stage to find types of cancer before they cause symptoms different techniques came into existence.  Researchers have been providing different innovative techniques and methods for cancer treatment. With the initiation of new techniques and methods in the field of medicine, a huge quantity of cancer disease data have been collected and are available to the medical study community. But the exact prediction of cancer is one of the remarkable and difficult tasks for doctors. For medical researchers, Machine Learning techniques and methods have become more popular. Machine Learning techniques can learn and recognize patterns and relationships between them from compound datasets, while they can successfully forecast future outcomes of a cancer disease. It is possible for early detection of cancer through machine learning where one can train the machine with previous data.

Nowadays Machine Learning techniques are being used in an extensive variety of applications ranging from identifying and classifying cancer via x-ray and CRT methods. According to the online statistics many articles have been published on the subject of Machine Learning and cancer disease. Still, the enormous majority of these papers are associated with using Machine Learning techniques to recognize, categorize, identify or discriminate cancer types and other tumours. The primary aim of cancer anticipates and prediction is different from the goals of cancer recognition and identification. Accomplishment in Machine Learning is not constantly assured. As with any technique, a good perceptive of the problem and approval of the restrictions of the data is important. Good quality of data is more important to get accurate results. The success rate in results occurs when we design and implement proper Machine Learning technique.

            Machine Learning (ML) techniques repeatedly learn and improve with familiarity. Learning means recognizing and understanding the input data and making intelligent decisions based on the datasets. It is very composite to supply all the decisions based on all possible input dataset. To attempt these types of problems, algorithms are suggested. These algorithms construct information from exact data and past knowledge with the ideology of logic, probability and statistics. There are several ways to execute techniques in Machine Learning, and commonly used methods are supervised and non supervised learning. One of the Machine Learning techniques is classification. It uses known data to determine how the new data should be classified into a set of existing categories. A classification is a form of supervised learning. Figure 1 depicts the classification working process.                                      

Literature Survey

In the world death rates are increased due to various types of cancers. Well, known types are lung cancer, breast cancer, blood cancer etc., and can be curable with early detection and treatment which varies from type to type.1 Scientist has a pack of information such as text, facts and images which are properly separated that can be used by doctors to identify the type of disease.2 Tumors can arise in any part of the body and can be transported to various other parts through blood flow in some cases. Early detection of its beginning stages could save a person’s life.3 million women every year are diagnosed with breast cancer, but most of them die due to late detection.4, 10 Various methods are used for detection and prognosis of cancer diseases.5 To discover hidden patterns and relationships advanced data mining techniques can be used.6 For cancer progression Machine Learning techniques are very useful.7 Artificial Intelligence has many branches which also includes Machine Learning that compiles various statistical probabilistic and optimization techniques that allow computers to learn from past datasets of various patterns.8 Early detection of malignant stages reduces the risk of cancer spreading.9 Many ML techniques are used to find the important risk factors. 11, 12 In medical sciences, ML techniques are very useful for solving prognostic and diagnostic problems. It is also useful in the extraction of knowledge from a huge amount of data. 13, 14

Proposed System

Cancer which is one of the deadliest diseases in today’s world has an effective way of reduction in its earliest stages. Its cure rate depends upon its time of detection. Many works have been going on worldwide, but each work lacks in many aspects such as intelligent prediction and inefficiency in implementing the Machine Learning based cancer prediction system.  The main intent of the paper is to propose a cancer prediction system that can predict the earliest stage by analyzing the minute set of attributes selected from the dataset.

In this paper, the constructed expert system named the cancer prediction system predicts cancer types (liver, thyroid, leukaemia, lymphoma, lung) which helps to predict cancer type also saving cost and time. Here considered the feature set of symptoms that includes lump area, pain region, swelling area, weight loss, appetite change, fever etc., and predict the class label to which the symptoms of an individual belongs to Lung, Liver, Leukaemia, Lymphoma, Thyroid, No cancer as the class labels. In our dataset, we will be filling the missing values by using mean (shown in figure 4), Calculating the non-missing value means in a column and replacing the missing values of each column separately independent from the others shown in figure 5 which can only be used with numeric data.  Accuracy can be predicted by the percentage of correctly classified instances.

Accuracy = (tp + tn) / (tp + tn + fp + fn)

where tp, fn, fp and tn represent the number of true positives, false negatives, false positives and true negatives respectively.

Recall is calculated as the ratio of the number of true positives divided by the sum of the true positives and the false negatives.

Recall = True Positive / (True Positive + False Negative)

           = True Positive / Total Actual Positive

The Roc curve or Receiver Operating Characteristic curve is a graphical representation that explains the diagnostic ability of a binary classifier system. Once the user enters the cancer prediction system, they need to provide symptoms. Then the prediction system analyzes the symptoms and displays the cancer type as shown in figure 2.

The cancer prediction system predicts the cancer type of the person based on the symptoms entered by the user. The proposed system uses a logistic regression classifier for training a machine learning model, which takes the symptoms from the user. Here we are adopting a logistic regression algorithm it works on the Data set (shown in figure 3) for training the machine learning supervised model which is used to predict the class label. Based on the class label predicted cancer type appear. Firstly consider a cancer dataset and select a classifier that has high accuracy level and recall score. Then we use that classifier for training and testing. The entered symptoms are recorded and according to them predict the cancer type. This Proposed system helps in the detection of a person’s tendency of cancer before going for clinical and lab tests which is costly and time-consuming. This proposed System generates accurate results which can be regarded with a good performance.

Adopted Logistic Regression statistical model is popular which is used for binary classification (example Yes or No, 0 or 1, etc.,) that is for predictions of the types. This is also used for multiclass classification. The hypothesis of logistic regression tends to limit the cost function between 0 and 1. The recall function is used to calculate the ratio of the number of true positives divided by the sum of the true positives and the false negatives. A true positive is an outcome where the model correctly predicts the positive class. A false negative is an outcome where the model incorrectly predicts the negative class. A ROC (Receiver Operating Characteristic) curve is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters True Positive Rate and False Positive Rate shown in figure 6.

Some of the main modules which are involved are

Accuracy-score (y_test,y_pred)

Recall-score (y_test, y_pred)

Roc-auc-score(y_test, y_pred)

Logistic Regression()

predict()

Conclusion

               In this world, Cancer becomes a catastrophe for a human being who is suffering from it. Now a day’s cancer is a tedious infection in the world. The most successful way to decrease cancer death is to identify it in the early stage. The premature identity of cancer can help cure the illness. So the latest technologies are used to detect the happening of cancer in the premature stage is growing. The main aim of this paper is to identify cancer type based on symptoms given by the user. Here we adopted a supervised learning algorithm and then used the Logistic Regression based on accuracy and recall score i.e., the algorithm which obtains high accuracy level and recalls score. In future, we are going to extend this work by finding the cancer stage and recommending different hospitals and doctors for the particular type of cancer. The advantages of the proposed system are executed with good performance because it generates accurate results.

Acknowledgement: Authors acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to authors/editors/publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed

Conflict of Interest:  The authors declare that they have no conflict of interest.

 Source of Funding:   Not Applicable

Authors’ Contribution:   The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.

References:

      [1] Roseline Jecintha I, Poonguzhali. Study on Data Mining Techniques for Cancer Prediction System. Int J Data Mining Techn Appl. 2018; 07(1): 60-63.

      [2] Malarvizhi. K, Rajivsuresh kumar G. An Instant Guidance on Cancer Prediction and Care Using Web Application. Int J Innov Techn Expl Engg. 2019; 8 (6S): 225-228.

      [3] Gousbi B, Mohamed Shanavas A R. A Study: Breast Cancer Prediction Using Data Mining Techniques. Asi J Comp Sci Tech. 2019; 8 (S2), 52-56.

      [4] priyanga A, prakasam S. The Role of Data Mining-Based Cancer prediction system (DMBCPS) in Cancer Awareness. Int J Compt Sci Engg Commun. 2013; 1(1): 381.

      [5] Samiksha Zaveri, Kamini Solanki. Data Mining Technique Used For Diagnosis and Prognosis of Cancer Disease. J Emerg Techn Innov Res. 2018; 5(11)

      [6] Eshlaghy, A.T, Poorebrahimi A,  Ebrahimi M, Razavi A. R, Ahmad L G. Using three machine learning techniques for predicting breast cancer recurrence. J  Heal Med  Inform. 2013; 4(2): 124

     [7] Konstantina Kourou, Themis P.Exarchos,  Konstantinos P.Exarchos, Michalis V.Karamouzis, Dimitrios I.Fotiadis.  Machine learning applications in cancer prognosis and prediction. Omputat Str Biotech J. 2015; 13: 8-17

     [8] Joseph A. Cruz, David S. Wishart. Applications of Machine Learning in Cancer Prediction and Prognosis. Cancer Informatics. 2007; 2: 59-77

     [9] Nath, A.S pal A, Mukhopadhyay S. A survey on cancer prediction and detection with data analysis. Innov Syst Softw Engg. 2019; 12(5): 185-187  https://doi.org/10.1007/s11334-019-00350-6

    [10] Yuanjie Zheng, Brad,M., Keller, Shonket Ray, Yan Wang, Emily F. Conant, James C. Gee, Despina        Kontos, Parenchymal. Texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment. Med Phys. 2015; https://doi.org/10.1118/s1.4921996

    [11] Chih-Jen Tseng, Chi-Jie LU, Chi-chang chang, Gin-Den chen. Application of Machine Learning to predict the recurrence-Proneness for cervical cancer. Neur Comp Appli. 2014; 21(3): 349-352. https://doi.org/10.1007/s00521-013-1359-1

    [12] Chi-chang chang, Ssu-Han Chen. Developing a Novel Machine Learning-Based Classification Scheme for Predicting SPCs in Breast Cancer Survivors. Front Gen. 2019; https://doi.org/s10.3389/fgene.2019.00848

    [13] Maalel, A., Hattab, M. Literature review: Overview of Cancer Treatment and Prediction Approaches based on Machine Learning: Smart Systems for E-Health. Adv Inf Know Proc Springer. 2019; p. 324

    [14] George D. Magoulas., Andriana Prentza. Machine Learning in Medical Applications 2049;  Springer LNCS; 2001.

Announcements

Dr. Pramod Kumar Manjhi joined Editor-in-Chief since July 2021 onwards

COPE guidelines for Reviewers

SCOPUS indexing: 2014, 2019 to 2021


Awards, Research and Publication incentive Schemes by IJCRR

Best Article Award: 

One article from every issue is selected for the ‘Best Article Award’. Authors of selected ‘Best Article’ are rewarded with a certificate. IJCRR Editorial Board members select one ‘Best Article’ from the published issue based on originality, novelty, social usefulness of the work. The corresponding author of selected ‘Best Article Award’ is communicated and information of award is displayed on IJCRR’s website. Drop a mail to editor@ijcrr.com for more details.

Women Researcher Award:

This award is instituted to encourage women researchers to publish her work in IJCRR. Women researcher, who intends to publish her research work in IJCRR as the first author is eligible to apply for this award. Editorial Board members decide on the selection of women researchers based on the originality, novelty, and social contribution of the research work. The corresponding author of the selected manuscript is communicated and information is displayed on IJCRR’s website. Under this award selected women, the author is eligible for publication incentives. Drop a mail to editor@ijcrr.com for more details.

Emerging Researcher Award:

‘Emerging Researcher Award’ is instituted to encourage student researchers to publish their work in IJCRR. Student researchers, who intend to publish their research or review work in IJCRR as the first author are eligible to apply for this award. Editorial Board members decide on the selection of student researchers for the said award based on originality, novelty, and social applicability of the research work. Under this award selected student researcher is eligible for publication incentives. Drop a mail to editor@ijcrr.com for more details.


Best Article Award

A Study by Humaira Tahir et al. entitled "Comparison of First Analgesic Demand after Major Surgeries of Obstetrics and Gynecology between Pre-Emptive Versus Intra-Operative Groups by Using Intravenous Paracetamol: A Cross-Sectional Study" is awarded Best Article for Vol 14 issue 14
A Study by Monica K. entitled "Risk Predictors for Lymphoma Development in Sjogren Syndrome - A Systematic Review" is awarded Best Article for Vol 14 issue 13
A Study by Mokhtar M Sh et al. entitled "Prevalence of Hospital Mortality of Critically Ill Elderly Patients" is awarded Best Article for Vol 14 issue 12
A Study by Vidya S. Bhat et al. entitled "Effect of an Indigenous Cleanser on the Microbial Biofilm on Acrylic Denture Base - A Pilot Study" is awarded Best Article for Vol 14 issue 11
A Study by Pandya S. et al. entitled "Acute and 28-Day Repeated Dose Subacute Toxicological Evaluation of Coroprotect Tablet in Rodents" is awarded Best Article for Vol 14 issue 10
A Study by Muhammad Zaki et al. entitled "Effect of Hemoglobin Level on the Severity of Acute Bronchiolitis in Children: A Case-Control Study" is awarded Best Article for Vol 14 issue 09
A Study by Vinita S & Ayushi S entitled "Role of Colour Doppler and Transvaginal Sonography for diagnosis of endometrial pathology in women presenting with Abnormal Uterine Bleeding" is awarded Best Article for Vol 14 issue 08
A Study by Prabhu A et al. entitled "Awareness of Common Eye Conditions among the ASHA (Accredited Social Health Activist) Workers in the Rural Communities of Udupi District- A Pilot Study" is awarded Best Article for Vol 14 issue 07
A Study by Divya MP et al. entitled "Non-Echoplanar Diffusion-Weighted Imaging and 3D Fiesta Magnetic Resonance Imaging Sequences with High Resolution Computed Tomography Temporal Bone in Assessment and Predicting the Outcome of Chronic Suppurative Otitis Media with Cholesteatoma" is awarded Best Article for Vol 14 issue 06
A Study by Zahoor Illahi Soomro et al. entitled "Functional Outcomes of Fracture Distal Radius after Fixation with Two Different Plates: A Retrospective Comparative Study" is awarded Best Article for Vol 14 issue 05
A Study by Ajai KG & Athira KN entitled "Patients’ Gratification Towards Service Delivery Among Government Hospitals with Particular Orientation Towards Primary Health Centres" is awarded Best Article for Vol 14 issue 04
A Study by Mbungu Mulaila AP et al. entitled "Ovarian Pregnancy in Kindu City, D.R. Congo - A Case Report" is awarded Best Article for Vol 14 issue 03
A Study by Maryam MJ et al. entitled "Evaluation Serum Chemerin and Visfatin Levels with Rheumatoid Arthritis: Possible Diagnostic Biomarkers" is awarded Best Article for Vol 14 issue 02
A Study by Shanthan KR et al. entitled "Comparison of Ultrasound Guided Versus Nerve Stimulator Guided Technique of Supraclavicular Brachial Plexus Block in Patients Undergoing Upper Limb Surgeries" is awarded Best Article for Vol 14 issue 01
A Study by Amol Sanap et al. entitled "The Outcome of Coxofemoral Bypass Using Cemented Bipolar Hemiarthroplasty in the Treatment of Unstable Intertrochanteric Fracture of Femur in a Rural Setup" is awarded Best Article Award of Vol 13 issue 24
A Study by Manoj KP et al. entitled "A Randomized Comparative Clinical Trial to Know the Efficacy of Ultrasound-Guided Transversus Abdominis Plane Block Against Multimodal Analgesia for Postoperative Analgesia Following Caesarean Section" is awarded Best Article Award of Vol 13 issue 23
A Study by Karimova II et al. entitled "Changes in the Activity of Intestinal Carbohydrases in Alloxan-Induced Diabetic Rats and Their Correction with Prenalon" is awarded Best Article of Vol 13 issue 22
A Study by Ashish B Roge et al. entitled "Development, Validation of RP-HPLC Method and GC MS Analysis of Desloratadine HCL and It’s Degradation Products" is awarded Best Article of Vol 13 issue 21
A Study by Isha Gaurav et al. entitled "Association of ABO Blood Group with Oral Cancer and Precancer – A Case-control Study" is awarded Best Article for Vol 13 issue 20
A Study by Amr Y. Zakaria et al. entitled "Single Nucleotide Polymorphisms of ATP-Binding Cassette Gene(ABCC3 rs4793665) affect High Dose Methotrexate-Induced Nephrotoxicity in Children with Osteosarcoma" is awarded Best Article for Vol 13 issue 19
A Study by Kholis Ernawati et al. entitled "The Utilization of Mobile-Based Information Technology in the Management of Dengue Fever in the Community Year 2019-2020: Systematic Review" is awarded Best Article for Vol 13 issue 18
A Study by Bhat Asifa et al. entitled "Efficacy of Modified Carbapenem Inactivation Method for Carbapenemase Detection and Comparative Evaluation with Polymerase Chain Reaction for the Identification of Carbapenemase Producing Klebsiella pneumonia Isolates" is awarded Best Article for Vol 13 issue 17
A Study by Gupta R. et al. entitled "A Clinical Study of Paediatric Tracheostomy: Our Experience in a Tertiary Care Hospital in North India" is awarded Best Article for Vol 13 issue 16
A Study by Chandran Anand et al. entitled "A Prospective Study on Assessment of Quality of Life of Patients Receiving Sorafenib for Hepatocellular Carcinoma" is awarded Best article for Vol 13 issue 15
A Study by Rosa PS et al. entitled "Emotional State Due to the Covid – 19 Pandemic in People Residing in a Vulnerable Area in North Lima" is awarded Best Article for Vol 13 issue 14
A Study by Suvarna Sunder J et al. entitled "Endodontic Revascularization of Necrotic Permanent Anterior Tooth with Platelet Rich Fibrin, Platelet Rich Plasma, and Blood Clot - A Comparative Study" is awarded Best Article for Vol 13 issue 13
A Study by Mona Isam Eldin Osman et al. entitled "Psychological Impact and Risk Factors of Sexual Abuse on Sudanese Children in Khartoum State" is awarded Best Article for Vol 13 issue 12
A Study by Khaw Ming Sheng & Sathiapriya Ramiah entitled "Web Based Suicide Prevention Application for Patients Suffering from Depression" is awarded Best Article for Vol 13 issue 11
A Study by Purushottam S. G. et al. entitled "Development of Fenofibrate Solid Dispersions for the Plausible Aqueous Solubility Augmentation of this BCS Class-II Drug" is awarded Best article for Vol 13 issue 10
A Study by Kumar S. et al. entitled "A Study on Clinical Spectrum, Laboratory Profile, Complications and Outcome of Pediatric Scrub Typhus Patients Admitted to an Intensive Care Unit from a Tertiary Care Hospital from Eastern India" is awarded Best Article for Vol 13 issue 09
A Study by Mardhiah Kamaruddin et al. entitled "The Pattern of Creatinine Clearance in Gestational and Chronic Hypertension Women from the Third Trimester to 12 Weeks Postpartum" is awarded Best Article for Vol 13 issue 08
A Study by Sarmila G. B. et al. entitled "Study to Compare the Efficacy of Orally Administered Melatonin and Clonidine for Attenuation of Hemodynamic Response During Laryngoscopy and Endotracheal Intubation in Gastrointestinal Surgeries" is awarded Best Article for Vol 13 issue 07
A Study by M. Muthu Uma Maheswari et al. entitled "A Study on C-reactive Protein and Liver Function Tests in Laboratory RT-PCR Positive Covid-19 Patients in a Tertiary Care Centre – A Retrospective Study" is awarded Best Article of Vol 13 issue 06 Special issue Modern approaches for diagnosis of COVID-19 and current status of awareness
A Study by Gainneos PD et al. entitled "A Comparative Evaluation of the Levels of Salivary IgA in HIV Affected Children and the Children of the General Population within the Age Group of 9 – 12 Years – A Cross-Sectional Study" is awarded Best Article of Vol 13 issue 05 Special issue on Recent Advances in Dentistry for better Oral Health
A Study by Alkhansa Mahmoud et al. entitled "mRNA Expression of Somatostatin Receptors (1-5) in MCF7 and MDA-MB231 Breast Cancer Cells" is awarded Best Article of Vol 13 issue 06
A Study by Chen YY and Ghazali SRB entitled "Lifetime Trauma, posttraumatic stress disorder Symptoms and Early Adolescence Risk Factors for Poor Physical Health Outcome Among Malaysian Adolescents" is awarded Best Article of Vol 13 issue 04 Special issue on Current Updates in Plant Biology to Medicine to Healthcare Awareness in Malaysia
A Study by Kumari PM et al. entitled "Study to Evaluate the Adverse Drug Reactions in a Tertiary Care Teaching Hospital in Tamilnadu - A Cross-Sectional Study" is awarded Best Article for Vol 13 issue 05
A Study by Anu et al. entitled "Effectiveness of Cytological Scoring Systems for Evaluation of Breast Lesion Cytology with its Histopathological Correlation" is awarded Best Article of Vol 13 issue 04
A Study by Sharipov R. Kh. et al. entitled "Interaction of Correction of Lipid Peroxidation Disorders with Oxibral" is awarded Best Article of Vol 13 issue 03
A Study by Tarek Elwakil et al. entitled "Led Light Photobiomodulation Effect on Wound Healing Combined with Phenytoin in Mice Model" is awarded Best Article of Vol 13 issue 02
A Study by Mohita Ray et al. entitled "Accuracy of Intra-Operative Frozen Section Consultation of Gastrointestinal Biopsy Samples in Correlation with the Final Histopathological Diagnosis" is awarded Best Article for Vol 13 issue 01
A Study by Badritdinova MN et al. entitled "Peculiarities of a Pain in Patients with Ischemic Heart Disease in the Presence of Individual Combines of the Metabolic Syndrome" is awarded Best Article for Vol 12 issue 24
A Study by Sindhu Priya E S et al. entitled "Neuroprotective activity of Pyrazolone Derivatives Against Paraquat-induced Oxidative Stress and Locomotor Impairment in Drosophila melanogaster" is awarded Best Article for Vol 12 issue 23
A Study by Habiba Suhail et al. entitled "Effect of Majoon Murmakki in Dysmenorrhoea (Usre Tams): A Standard Controlled Clinical Study" is awarded Best Article for Vol 12 issue 22
A Study by Ghaffar UB et al. entitled "Correlation between Height and Foot Length in Saudi Population in Majmaah, Saudi Arabia" is awarded Best Article for Vol 12 issue 21
A Study by Siti Sarah Binti Maidin entitled "Sleep Well: Mobile Application to Address Sleeping Problems" is awarded Best Article for Vol 12 issue 20
A Study by Avijit Singh"Comparison of Post Operative Clinical Outcomes Between “Made in India” TTK Chitra Mechanical Heart Valve Versus St Jude Mechanical Heart Valve in Valve Replacement Surgery" is awarded Best Article for Vol 12 issue 19
A Study by Sonali Banerjee and Mary Mathews N. entitled "Exploring Quality of Life and Perceived Experiences Among Couples Undergoing Fertility Treatment in Western India: A Mixed Methodology" is awarded Best Article for Vol 12 issue 18
A Study by Jabbar Desai et al. entitled "Prevalence of Obstructive Airway Disease in Patients with Ischemic Heart Disease and Hypertension" is awarded Best Article for Vol 12 issue 17
A Study by Juna Byun et al. entitled "Study on Difference in Coronavirus-19 Related Anxiety between Face-to-face and Non-face-to-face Classes among University Students in South Korea" is awarded Best Article for Vol 12 issue 16
A Study by Sudha Ramachandra & Vinay Chavan entitled "Enhanced-Hybrid-Age Layered Population Structure (E-Hybrid-ALPS): A Genetic Algorithm with Adaptive Crossover for Molecular Docking Studies of Drug Discovery Process" is awarded Best article for Vol 12 issue 15
A Study by Varsha M. Shindhe et al. entitled "A Study on Effect of Smokeless Tobacco on Pulmonary Function Tests in Class IV Workers of USM-KLE (Universiti Sains Malaysia-Karnataka Lingayat Education Society) International Medical Programme, Belagavi" is awarded Best article of Vol 12 issue 14, July 2020
A study by Amruta Choudhary et al. entitled "Family Planning Knowledge, Attitude and Practice Among Women of Reproductive Age from Rural Area of Central India" is awarded Best Article for special issue "Modern Therapeutics Applications"
A study by Raunak Das entitled "Study of Cardiovascular Dysfunctions in Interstitial Lung Diseas epatients by Correlating the Levels of Serum NT PRO BNP and Microalbuminuria (Biomarkers of Cardiovascular Dysfunction) with Echocardiographic, Bronchoscopic and HighResolution Computed Tomography Findings of These ILD Patients" is awarded Best Article of Vol 12 issue 13 
A Study by Kannamani Ramasamy et al. entitled "COVID-19 Situation at Chennai City – Forecasting for the Better Pandemic Management" is awarded best article for  Vol 12 issue 12
A Study by Muhammet Lutfi SELCUK and Fatma entitled "Distinction of Gray and White Matter for Some Histological Staining Methods in New Zealand Rabbit's Brain" is awarded best article for  Vol 12 issue 11
A Study by Anamul Haq et al. entitled "Etiology of Abnormal Uterine Bleeding in Adolescents – Emphasis Upon Polycystic Ovarian Syndrome" is awarded best article for  Vol 12 issue 10
A Study by entitled "Estimation of Reference Interval of Serum Progesterone During Three Trimesters of Normal Pregnancy in a Tertiary Care Hospital of Kolkata" is awarded best article for  Vol 12 issue 09
A Study by Ilona Gracie De Souza & Pavan Kumar G. entitled "Effect of Releasing Myofascial Chain in Patients with Patellofemoral Pain Syndrome - A Randomized Clinical Trial" is awarded best article for  Vol 12 issue 08
A Study by Virendra Atam et. al. entitled "Clinical Profile and Short - Term Mortality Predictors in Acute Stroke with Emphasis on Stress Hyperglycemia and THRIVE Score : An Observational Study" is awarded best article for  Vol 12 issue 07
A Study by K. Krupashree et. al. entitled "Protective Effects of Picrorhizakurroa Against Fumonisin B1 Induced Hepatotoxicity in Mice" is awarded best article for issue Vol 10 issue 20
A study by Mithun K.P. et al "Larvicidal Activity of Crude Solanum Nigrum Leaf and Berries Extract Against Dengue Vector-Aedesaegypti" is awarded Best Article for Vol 10 issue 14 of IJCRR
A study by Asha Menon "Women in Child Care and Early Education: Truly Nontraditional Work" is awarded Best Article for Vol 10 issue 13
A study by Deep J. M. "Prevalence of Molar-Incisor Hypomineralization in 7-13 Years Old Children of Biratnagar, Nepal: A Cross Sectional Study" is awarded Best Article for Vol 10 issue 11 of IJCRR
A review by Chitra et al to analyse relation between Obesity and Type 2 diabetes is awarded 'Best Article' for Vol 10 issue 10 by IJCRR. 
A study by Karanpreet et al "Pregnancy Induced Hypertension: A Study on Its Multisystem Involvement" is given Best Paper Award for Vol 10 issue 09

List of Awardees

A Study by Ese Anibor et al. "Evaluation of Temporomandibular Joint Disorders Among Delta State University Students in Abraka, Nigeria" from Vol 13 issue 16 received Emerging Researcher Award


A Study by Alkhansa Mahmoud et al. entitled "mRNA Expression of Somatostatin Receptors (1-5) in MCF7 and MDA-MB231 Breast Cancer Cells" from Vol 13 issue 06 received Emerging Researcher Award


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