Guava Disease Detection Using Deep Convolutional Neural Networks: A Case Study of Guava Plants

Food production is a growing challenge with the increasing global population. To increase the yield of food production, we need to adopt new biotechnology-based fertilization techniques. Furthermore, we need to improve early prevention steps against plant disease. Guava is an essential fruit in Asian countries such as Pakistan, which is fourth in its production. Several pathological and fungal diseases attack guava plants. Furthermore, postharvest infections might result in significant output losses. A professional opinion is essential for disease analysis due to minor variances in various guava disease symptoms. Farmers’ poor usage of pesticides may result in financial losses due to incorrect diagnosis. Computer-vision-based monitoring is required with developing field guava plants. This research uses a deep convolutional neural network (DCNN)-based data enhancement using color-histogram equalization and the unsharp masking technique to identify different guava plant species. Nine angles from 360∘ were applied to increase the number of transformed plant images. These augmented data were then fed as input into state-of-the-art classification networks. The proposed method was first normalized and preprocessed. A locally collected guava disease dataset from Pakistan was used for the experimental evaluation. The proposed study uses five neural network structures, AlexNet, SqueezeNet, GoogLeNet, ResNet-50, and ResNet-101, to identify different guava plant species. The experimental results proved that ResNet-101 obtained the highest classification results, with 97.74% accuracy.

Adenolipoma of the Breast: A Case Report

Adenolipoma of the breast is a rare tumor classified as a hamartomatous lesion. It is a well-circumscribed lesion composed of adipocytes and other breast tissues. The characteristic feature is a well-circumscribed mass containing radiolucent fat admixed with dense fibrous connective tissue surrounded by a thin radiopaque pseudo capsule. Microscopically, there is a mixture of ducts and lobules with adipose tissue. Ductal hyperplasia, adenosis, calcification, and apocrine metaplasia may occur within the hamartoma. These are rarely associated with malignancies and excision is considered curative. If these lesions are not detected clinically or radiologically, these remain unrecognized. Awareness of this poorly recognized benign entity would help avoid an incorrect diagnosis and unnecessary intervention. Here we present a case of a 35-year-old female diagnosed histologically as adenolipoma of the breast.

Successful endovascular coiling of infectious cerebral aneurysm following Staphylococcus haemolyticus endocarditis

Recent reports suggest that Staphylococcus haemolyticus can cause infective endocarditis (IE). However, no data are available regarding infectious intracranial aneurysm (IIA) following S. haemolyticus endocarditis. Endovascular coiling is a challenging approach for the treatment of IIA. We describe the case of a 63-year-old woman who suddenly developed aphasia and dysarthria following an acute cerebral infarction in her left insular and temporal cortex. After a total hysterectomy at the age of 39, the patient had suffered from recurrent bacterial pyomyositis in her legs. At admission, there was no evidence of cerebral aneurysm, as assessed by magnetic resonance angiography, and no vegetation, as assessed by transesophageal echocardiography (TEE), resulting in an incorrect diagnosis. However, subarachnoid hemorrhage and development of cerebral aneurysm in the left middle cerebral artery occurred within 1 week of hospitalization. Continuous positive blood culture results and a second TEE finally revealed that IE was caused by S. haemolyticus. Coil embolization of the IIA was successful on day 26 after symptom onset; after this procedure, the patient began to recover. This case demonstrates that S. haemolyticus-induced endocarditis can cause IIA. Endovascular coiling is a potentially effective approach to treat IIA.

Spontaneous rupture of a cystic-degenerated kidney

Clinical diagnosis of rupture of a cystic-degenerated kidney in non-traumatic cases is difficult, which often leads to an incorrect diagnosis. We observed 3 patients with spontaneous rupture of the cystic-degenerated kidney.

Marasmus and stunting in 2-month-old boy with pneumatocele

BackgroundNutrition is essential for humans and if inadequate may lead to undernutrition. Undernourished children are very susceptible to infections, such as pneumonia, one of its complications being pneumatocele, which is a more severe condition. Pulmonary pneumatoceles are thin-walled, air-filled cysts that develop within the lung parenchyma and have been found in 2.4 percent of 493 infants and children with pneumonia. However, in staphylococcal pneumonias, the frequency of pneumatocele can reach as high as 85 percent. Infants and young children are more likely to have pneumatoceles. It is critical to distinguish marasmus with pneumatocele from many other similar diagnoses. Failure to recognize can lead to incorrect diagnosis and treatment, causing more harm than good to patient care. This case highlights the importance of maintaining a high suspicion of pneumonia in neonates even with normal radiological findings and of searching for pneumatoceles. Case DescriptionWe report a case of marasmus and stunting accompanied by pneumatocele in a 2-month-old boy. The diagnosis was made based on history, physical examination, anthropometric examination using the WHO child growth standards, laboratory tests, and radiological imaging. Management of the patient was according to a multidisciplinary system including antibiotics administration and wasting management. ConclusionPneumatoceles are serious complications after pneumonia. Pneumonia is common in children with marasmus. Children with marasmus are caused by various underlying factors. The progression begins in the womb and continues through the first 1000 days of life.

Evaluation of Pain in Adults With Childhood-Onset Disabilities and Communication Difficulties

Adults with childhood-onset disabilities, particularly those with central nervous system impairment, commonly experience pain. Because many such individuals have difficulties in communication, caregivers and medical professionals must identify and interpret non-verbal behaviors as indicators of pain. This process is challenging and can lead to poor outcomes through delayed or incorrect diagnosis and treatment. Most research in the evaluation of pain in individuals with neurologic impairment has focused on the pediatric population, and evidence-based guidelines do not exist for adults. The purpose of this paper is to review current recommendations for pain assessment in adults with communication impairment. This approach includes guidance for history-taking, pharmacologic review, physical examination, and the judicious use of laboratory and imaging tests. Finally, we discuss adult-specific diagnoses to consider when evaluating pain in adults with childhood-onset disabilities and communication difficulties.

Lipoedema as a Social Problem. A Scoping Review

(1) Background: Lipoedema is a disease characterized by excessive bilateral and symmetrical accumulation of subcutaneous tissue in the lower extremities. It is a poorly understood condition, and low awareness of its existence often leads to incorrect diagnosis Initially, lipoedema was considered to be completely independent of lifestyle Currently, however, more and more cases of the coexistence of lipoedema and obesity are described in the literature as additionally affecting the severity of the disease The aim of the review is to present lipoedema as a social problem. (2) Methods: Materials on lipoedema in the social context were selected from 2018–2021. The PRISMA-Scr checklist was used in the review. (3) Results: Research has shown that more than 3/4 of patients with lipoedema are also overweight or obese. Patients with lipoedema have many comorbidities, and their presence negatively affects the quality of life. The quality of life in patients with lipoedema is lower than in healthy patients. (4) Conclusions: The number of studies available on lipoedema is low. Obesity is common in patients with lipoedema. Mental disorders increase the level of experienced pain. Lipoedema significantly reduces quality of life. A healthy lifestyle in patients with lipoedema could be helpful for prevention of complications and disability.

Anorectal emergencies: WSES-AAST guidelines

Anorectal emergencies comprise a wide variety of diseases that share common symptoms, i.e., anorectal pain or bleeding and might require immediate management. While most of the underlying conditions do not need inpatient management, some of them could be life-threatening and need prompt recognition and treatment. It is well known that an incorrect diagnosis is frequent for anorectal diseases and that a delayed diagnosis is related to an impaired outcome. This paper aims to improve the knowledge and the awareness on this specific topic and to provide a useful tool for every physician dealing with anorectal emergencies.The present guidelines have been developed according to the GRADE methodology. To create these guidelines, a panel of experts was designed and charged by the boards of the World Society of Emergency Surgery (WSES) and American Association for the Surgery of Trauma (AAST) to perform a systematic review of the available literature and to provide evidence-based statements with immediate practical application. All the statements were presented and discussed during the WSES-AAST-WJES Consensus Conference on Anorectal Emergencies, and for each statement, a consensus among the WSES-AAST panel of experts was reached. We structured our work into seven main topics to cover the entire management of patients with anorectal emergencies and to provide an up-to-date, easy-to-use tool that can help physicians and surgeons during the decision-making process.

Performance Comparison of Deep CNN Models for Disease Diagnosis on Apple Leaves

The apple is one of the most cultivated fruits in the world. They are round in shape and their color varies from green to red. Apple Orchards face constant threats from a large number of insects and pathogens and the early detection of these diseases can help in mitigating these harmful effects. An apple tree takes around six to ten years to mature and produce fruit and therefore, the production costs are high and there is no room for such diseases to get a healthy fruit and a profitable yield. Delayed or incorrect diagnosis of these diseases can lead to using either inadequate or more than required chemicals or using a wrong chemical altogether to treat the plant. Historically, this problem was solved using conventional machine learning algorithms like SVMs, Decision Trees and Random Forests. However, in recent times, the approach to solve this problem has shifted to deep learning, specifically Convolutional Neural Networks. CNN’s are powerful tools that can be used for image classification. We can get state-ofthe-art results even by using small amounts of data and little to no data preprocessing. In this work, we are going to compare some of the state of the art CNN architectures on the task of accurately classifying a given image into different categories of diseases or as a healthy leaf. Finally, experimental results are conveyed and performance analysis of these various architectures has been done.