Diagnosis of Prostate Cancer Using GLCM Enabled KNN Technique by Analyzing MRI Images

Cancer has a disproportionately large influence on the death rate of adults. A patient needs to get a diagnosis of their condition as quickly as is humanly feasible in order to have the greatest chance of surviving their sickness. Skilled medical professionals use medical imaging and other traditional diagnostic methods to search for clues that may indicate the presence of malignant tendencies inside the body. Nevertheless, manual diagnosis may be time-consuming and subjective owing to the wide range of interobserver variability induced by the enormous number of medical imaging data. This variability is caused by the fact that medical imaging data are collected. Because of this, the process of accurately diagnosing a patient could become more difficult. To execute jobs that included machine learning and the interpretation of complicated imagery, cutting-edge computer technology was necessary. Since the 1980s, researchers have been working on developing a computer-aided diagnostic system that would help medical professionals in the early diagnosis of various malignancies. According to the most recent projections, prostate cancer will be discovered in the body of one out of every seven men at some time throughout the course of their life. It is unacceptable how many men are being told that they have prostate cancer, and the condition is responsible for the deaths of a rising number of men every year. Because of the high quality and multidimensionality of the MRI pictures, you will also need a powerful diagnosis system in addition to the CAD tools. Since it has been shown that CAD technology is beneficial, researchers are looking at methods to improve the accuracy, precision, and speed of the systems that use it. The effectiveness of CAD technology has been shown. This research proposes a strategy that is both effective and efficient for the processing of images and the extraction of features as well as for machine learning. This work makes use of MRI scans and machine learning in an effort to detect prostate cancer at an early stage. Histogram equalization is used while doing the preliminary processing on photographs. The image's overall quality is elevated as a result. The fuzzy C means approach is used in order to segment the images. Using a Gray Level Cooccurrence Matrix (GLCM), it is feasible to extract features from a dataset. The KNN, random forest, and AdaBoost classification algorithms are used in the classification process.

Integrating bio medical sensors in detecting hidden signatures of COVID-19 with Artificial intelligence

Today COVID-19 pandemic articulates high stress on clinical resources around the world. At present, physical and viral tests are slowly emerging, and there is a need for robust pandemic detection that biomedical sensors can aid. The utility of biomedical sensors is correlated with the medical instruments with physiological metrics. These Biomedical sensors are integrated with the systematic device to track the target analytes with a biomedical component. The COVID-19 patients' samples are collected, and biomarkers are detected using four sensors: blood pressure sensor, G-FET based biosensor, electrochemical sensor, and potentiometric sensor with different quantifiable measures. The imputed data is then profiled with chest X-ray images from the Covid-19 patients.Multi-Layer Perceptron (MLP), an AI model, is deployed to identify the hidden signatures with biomarkers. The performance of the biosensor is measured with three parameters such as sensitivity, specificity and detection limit by generating the calibration plots that accurately fits the model.

Hospital-Based Contact Tracing of Patients With COVID-19 and Health Care Workers During the COVID-19 Pandemic in Eastern India: Cross-sectional Study

Background

The contact tracing and subsequent quarantining of health care workers (HCWs) are essential to minimizing the further transmission of SARS-CoV-2 infection and mitigating the shortage of HCWs during the COVID-19 pandemic situation.

Objective

This study aimed to assess the yield of contact tracing for COVID-19 cases and the risk stratification of HCWs who are exposed to these cases.

Methods

This was an analysis of routine data that were collected for the contact tracing of COVID-19 cases at the All India Institute of Medical Sciences, Bhubaneswar, in Odisha, India. Data from March 19 to August 31, 2020, were considered for this study. COVID-19 cases were admitted patients, outpatients, or HCWs in the hospital. HCWs who were exposed to COVID-19 cases were categorized, per the risk stratification guidelines, as high-risk contacts or low-risk contacts

Results

During contact tracing, 3411 HCWs were identified as those who were exposed to 360 COVID-19 cases. Of these 360 cases, 269 (74.7%) were either admitted patients or outpatients, and 91 (25.3%) were HCWs. After the risk stratification of the 3411 HCWs, 890 (26.1%) were categorized as high-risk contacts, and 2521 (73.9%) were categorized as low-risk contacts. The COVID-19 test positivity rates of high-risk contacts and low-risk contacts were 3.8% (34/890) and 1.9% (48/2521), respectively. The average number of high-risk contacts was significantly higher when the COVID-19 case was an admitted patient (number of contacts: mean 6.6) rather than when the COVID-19 case was an HCW (number of contacts: mean 4.0) or outpatient (number of contacts: mean 0.2; P=.009). Similarly, the average number of high-risk contacts was higher when the COVID-19 case was admitted in a non–COVID-19 area (number of contacts: mean 15.8) rather than when such cases were admitted in a COVID-19 area (number of contacts: mean 0.27; P<.001). There was a significant decline in the mean number of high-risk contacts over the study period (P=.003).

Conclusions

Contact tracing and risk stratification were effective and helped to reduce the number of HCWs requiring quarantine. There was also a decline in the number of high-risk contacts during the study period. This indicates the role of the implementation of hospital-based, COVID-19–related infection control strategies. The contact tracing and risk stratification approaches that were designed in this study can also be implemented in other health care settings.

Genomic sequence analysis of lung infections using artificial intelligence technique

Attributable to the modernization of Artificial Intelligence (AI) procedures in healthcare services, various developments including Support Vector Machine (SVM), and profound learning. For example, Convolutional Neural systems (CNN) have prevalently engaged in a significant job of various classificational investigation in lung malignant growth, and different infections. In this paper, Parallel based SVM (P-SVM) and IoT has been utilized to examine the ideal order of lung infections caused by genomic sequence. The proposed method develops a new methodology to locate the ideal characterization of lung sicknesses and determine its growth in its early stages, to control the growth and prevent lung sickness. Further, in the investigation, the P-SVM calculation has been created for arranging high-dimensional distinctive lung ailment datasets. The data used in the assessment has been fetched from real-time data through cloud and IoT. The acquired outcome demonstrates that the developed P-SVM calculation has 83% higher accuracy and 88% precision in characterization with ideal informational collections when contrasted with other learning methods.

LED fluorescence microscopy increases the detection of smear-positive pulmonary tuberculosis in medical colleges of India

In July 2012, light-emitting diode fluorescence microscopy (LED-FM) replaced conventional light microscopy using Ziehl-Neelsen stain in the detection of sputum-positive pulmonary tuberculosis in 190 microscopy centres of medical colleges operating under India's Revised National Tuberculosis Control Programme. We compared the performance of LED-FM (July-December 2012) to that of conventional microscopy (July-December 2011) across 190 sites. Of 222 658 patients examined using conventional microscopy, 28 042 (12.6%) were smear-positive, while of 224 714 examined using LED-FM, 33 552 (14.9%) were smear-positive, an additional yield of 5251 cases after adjusting for the increase in patients examined. We recommend replacing conventional microscopy with LED-FM in high workload microscopy centres in India.

Percutaneous ultrasound-guided fine-needle aspiration of portal vein thrombi as a diagnostic and staging technique for hepatocellular carcinoma

BACKGROUND

Detection of portal vein tumor invasion in hepatocellular carcinoma (HCC) is important in determining therapy and prognosis. Patients with portal vein thrombus (PVT) due to tumor are considered to have advanced disease and are only offered palliative therapy. Therefore, every possible attempt should be made to accurately differentiate benign from malignant PVT.

METHODS

In this study, 20 patients presenting to the out-patient department with a PVT and a diagnosis/diagnostic suspicion of HCC were subjected to FNAC of PVT. Clinical, cytological, and histopathological data for these patients were analyzed.

RESULTS

The patients had a median age of 58 years, with majority being cirrhotic (80%) and males (80%). Thirteen patients had a prior radiological diagnosis of HCC at the time of FNAC. In three patients without any mass on imaging, FNAC made the initial diagnosis and staged the disease simultaneously. 50% of the thrombi were limited to 1st-order portal vein branches (vp3). Sixteen of the aspirates were positive for malignancy with 50% of the tumors being moderately differentiated. On histologic follow-up, three of the patients with negative aspirates had bland thrombi in their portal veins. No complications resulted from the procedure.

CONCLUSIONS

FNAC of PVT is a simple, safe, effective, well-tolerated, and economical method for staging of patients with HCC. When used as the initial diagnostic procedure, in selected patients, it can provide the diagnosis and staging information simultaneously.

Dietary factors in pathogenesis of gallstone disease in southern India--a hospital-based case-control study

BACKGROUND

Pigment or mixed gallstones are common in southern India. The etiology is not established. Known risk factors include an obese, diabetic female and a nonsmoker male.

AIM

To determine the association of dietary factors with mixed/pigment gallstones amongst southern Indian patients.

METHODS

Diet details were obtained from 346 patients (178 women) with gallstones and an equal number of healthy controls who were age- and sex-matched attendants of the patients, sharing similar socioeconomic and demographic characteristics, with normal abdominal ultrasonogram. Data recorded included the number of daily meals, nature of cereal used, vegetarianism, oil consumed per month, sugar consumption per day, tamarind (Garcinia camborginia ) usage per week, and per-day beverage consumption.

RESULTS

There was no difference between cases and controls in consumption of non-vegetarian food, type of cereal, average oil and sugar consumption, and type of beverage consumed (tea/coffee/milk/combination). Individuals with BMI> 22 were at higher risk to develop gallstones (OR 1.49; 95% CI 1.09, 2.04; p=0.01). There was significant risk of gallstone formation with the use of tamarind when consumed > 3 times a week (OR 1.76; 95% CI 1.05, 2.96; p=0.03). Higher BMI and tamarind use were significant risk factors even on multivariate logistic regression analysis (p=0.02).

CONCLUSION

Higher BMI and use of tamarind, a common ingredient of diet in southern India, are risk factors in the formation of gallstones in southern India.

Oat cell carcinoma of the oesophagus--a case report and review of literature

A 45-year-old male presented with dysphagia, anorexia and progressive weight loss. He was a chronic smoker. Oesophagoscopy showed an ulceroproliferative growth of 25-30 cm size. Histopathology from the biopsy tissue showed small cell (oat cell) carcinoma. He received radiotherapy, but died 9 months later. Small cell carcinoma of the oesophagus constitutes 0.8-2.4% of all the oesophageal carcinoma. The tumour is an aggressive one with a poor prognosis irrespective of the treatment.

Seizure with single-pulse transcranial magnetic stimulation in a 35-year-old otherwise-healthy patient with bipolar disorder

This case report describes a patient who developed a seizure with single-pulse transcranial magnetic stimulation during motor threshold estimation. The patient had no history of seizures in the past and no gross neurologic deficits. The only possible seizure-provoking factors were modest doses of lithium and chlorpromazine, which the patient was on, and family history of seizure in a brother. This report aims to highlight the fact that single-pulse transcranial magnetic stimulation may provoke a seizure even in the absence of gross neurologic abnormality.

Risk factors for esophageal cancer in Coimbatore, southern India: a hospital-based case-control study

BACKGROUND

Cancer of the esophagus is common in India. The risk factors predisposing to cancer in southern Indian patients are not known.

AIM

To determine the role of smoking, alcohol and their combination, and diet factors in the etiology of cancer of the esophagus.

METHODS

Risk factors like alcohol consumption, smoking, tobacco chewing, and pre-illness diet details in 90 patients with cancer of the esophagus were compared with those in age- and sex-matched control subjects.

RESULTS

The risk for esophageal cancer was 3.5 times higher with alcohol consumption, 2.5 times higher for tobacco users, and 2.8 times higher each for betel nut chewers and smokers. The calculated odds ratio for the social habits and diet factors was significant amongst cases of cancer esophagus.

CONCLUSION

Alcoholism, smoking, and chewing of tobacco are factors predisposing to esophageal cancer in southern India.

Acquired volvulus following Nissen fundoplication

Nissen fundoplication is the procedure of choice for the management of gastroesophageal reflux disease. We report a case of acquired gastric volvulus following open fundoplication. The mechanism of formation and correction of the volvulus is discussed.

Prevalence and epidemiologic characteristics of opportunistic and non-opportunistic intestinal parasitic infections in HIV positive patients in Manipur

A survey of the intestinal parasites among the HIV positive asymptomatic injecting drug users (IDUs) in Manipur State in North-east India revealed the presence of three protozoan and two nematode species. Of these, the two opportunistic parasitic protozoans i.e., Cryptosporidium sp. (94.4 percent) and Isospora sp. (10.7 percent) were predominant over Entamoeba histolytica (5.6 percent), while non-opportunistic parasitic nematodes, i.e. Ascaris lumbricoides (4.6 percent) and Ancylostoma sp. (1 percent) were the less frequently detected ones. In all cases, the fungal flora were predominant. Candida sp. was more often encountered compared to Cladosporium and Humicloa. The study also revealed that although these individuals showed no gastro-intestinal disorders like diarrhoea, they still harbour these opportunistic and non-opportunistic parasites and act as carriers, particularly of the former category, in the community via contaminated water and open defaecation practices.

Cryptosporidiosis in HIV infection

Preserved faecal specimens (10 per cent Buffer formalin), from 150 HIV infected persons having symptomatic diarrhoea and 50 non-diarrhoeal apparently healthy people aged between 15-30 years were examined to detect the presence of cryptosporidium infection. 70 diarrhoeal patients (46.6 per cent) were found to excrete this pathogen. None of the non-diarrhoeals was found to excrete this parasite. It is evident from the present study that cryptosporidium is highly prevalent amongst the HIV infected persons with symptomatic diarrhoea. All the HIV infected persons were known cases of injected drug users.

Purification and properties of xylanase from the thermophilic fungus, Humicola lanuginosa (Griffon and Maublanc) Bunce

An extracellular xylanase was purified to homogeneity from the culture filtrate of the thermophilic fungus, Humicola lanuginosa (Griffon and Maublanc) Bunce and its properties were studied. A fourfold purification and a yield of 8% were achieved. The molecular weight of the protein was found to be 22,500 based on electrophoretic mobility and 29,000 by gel filtration behavior. The protein is rich in acidic amino acids, glycine and tyrosine, and poor in sulfur-containing amino acids. The kinetic properties of the enzyme are similar to those of other fungal xylanases. The enzyme shows high affinity toward larchwood xylan (Km = 0.91 mg/ml) and hydrolyzes only xylan. The enzyme becomes inactivated when stored for more than 2 months at -20 degrees C in the dry state. Such an inactivation has not been reported so far for any xylanase. Using chromatographic techniques, one species of protein differing from the native protein in charge but enzymatically active was isolated in low yields. However, a large molecular-weight species of the protein devoid of enzyme activity was isolated in substantial quantities and further characterized. Based on ultracentrifugation and gel electrophoretic studies, it was concluded that this species may be an aggregate of the native protein and that such an aggregation might be taking place on storage in the dry state at -20 degrees C, leading to loss in activity.