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- Randomized Placebo Controlled Open Labelled Comparison of Efficacy of Diclofenac Transdermal Patch in Post Operative Pain
Abstract Views :196 |
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Authors
Niranjan Salunke
1,
Maniram Kranthi Kumar
1,
Yogesh
2,
Meher Tabassum
3,
P. Pravallika
3,
M. Sampoorna
3,
Pranay Rao
3
Affiliations
1 Durgabai Deshmukh Hospital, 1-9-27, Osmania University Rd, Vidya Nagar, Adikmet, Hyderabad, Telangana, IN
2 Bharath School of Pharmacy, Mangalpally, Ibrahimpatnam, Telangana, IN
3 Department of Pharmacy, Bharath School of Pharmacy, Mangalpally, Ibrahimpatnam, Telangana, IN
1 Durgabai Deshmukh Hospital, 1-9-27, Osmania University Rd, Vidya Nagar, Adikmet, Hyderabad, Telangana, IN
2 Bharath School of Pharmacy, Mangalpally, Ibrahimpatnam, Telangana, IN
3 Department of Pharmacy, Bharath School of Pharmacy, Mangalpally, Ibrahimpatnam, Telangana, IN
Source
Research Journal of Pharmacy and Technology, Vol 12, No 3 (2019), Pagination: 1119-1121Abstract
Postoperative incisional pain is a common form of acute pain. Recent studies demonstrate that about 50–70% of patients experience moderate to severe pain after surgery. Reasons for this quandary are distinct mechanisms of incisional nociception compared to other pain conditions or lack of an in depth knowledge about the pathophysiology and neuropharmacology of postoperative pain. Acute postoperative pain is followed by chronic pain in 10–50% of individuals which can be severe in about 2-10% of patients undergoing common operations such as groin hernia repair, breast and thoracic surgery, leg amputation, and coronary artery bypass surgery. Therefore, persistent postsurgical pain represents a major, largely unrecognised clinical problem. Iatrogenic neuropathic pain is probably the most important cause of long-term postsurgical pain. Consequently, surgical techniques that avoid nerve damage should be applied whenever possible. Major surgical operations are still followed by pain, organ dysfunction and prolonged convalescence. It has been assumed that sufficient pain relief will improve the surgical outcome with reduced morbidity, need for hospitalization and convalescence. It has been realized that several other factors in perioperative management are important in the control of postoperative recovery and rehabilitation, and that these factors must be considered and revised in order to achieve the advantageous effects of pain relief on outcome. Among the most commonly used pain-relieving techniques [patient-controlled analgesia (PCA) with opioids, non-steroidal anti-inflammatory drugs (NSAIDs) and epidural analgesic techniques], there is evidence that the epidural local anaesthetic or local anaesthetic–opioid techniques are the most effective on providing dynamic pain relief after major surgical procedures. The goal of postoperative pain management is to relieve the pain while keeping side effects to a minimum. This can be best accomplished with a multimodal approach. Minimally invasive surgery and enhanced recovery protocols have addressed pain management in terms of these goals.Keywords
Postoperative Incisional Pain, Bypass Surgery, Pain Management, Transdermal Patch, Postoperative Recovery and Rehabilitation.References
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- Convolutional neural network architecture for detection and classification of diseases in fruits
Abstract Views :266 |
PDF Views:122
Authors
Affiliations
1 Amity University, Noida 201 313, IN
1 Amity University, Noida 201 313, IN
Source
Current Science, Vol 122, No 11 (2022), Pagination: 1315-1320Abstract
Artificial intelligence is now becoming a part of people’s everyday lives. It can help farmers detect any disease in the early stage and take pre-emptive actions to save their crops and control disease spread, thus preventing crop wastage as well as increasing their income. The present study uses a combination of 13 convolutional neural network (CNN) models to classify five types of fruits and their leaf images into 41 classes, including diseased and healthy. Results show that the average accuracy of this CNN architecture is above 90% for all 13 individual models. One of the CNN models has been compared with three pre-trained models, i.e. MobileNet, DenseNet121 and InceptionV3 trained using the same dataset. It shows that the CNN architecture used in this study has higher accuracy while also being simple and easy to train.Keywords
Agriculture, Artificial Intelligence, Convolutional Neural Network, Deep Learning, Fruit and Leaf Disease DetectionReferences
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