Of all suspicious pigmented skin lesions considered for analysis, a large portion is often benign. The pressure of pathology services and secondary care must be reduced throughout the patient trials using modern techniques for improving the melanoma diagnosis accuracy. Dermoscopic images obtained from digital single-lens reflex (DSLR) cameras, smartphones and a lightweight USB camera are compared using artificial intelligence (AI) algorithm for determining the accuracy of melanoma identification. Datasets are obtained from thousand test samples undergoing plastic surgery. The diagnostic trial is masked, single arm and multicentered. The controlled and suspicious skin lesions as well as the suspicious pigmented skin lesion are captured on the aforementioned cameras while scheduling for biopsy. The possibility of melanoma is assessed using deep learning (DL) techniques on the pigmented skin lesions seen in the dermascopic images for identifying melanoma. For this purpose, we train a deterministic AI algorithm based on malignancy recognition by deep ensemble and inputs from clinicians. The histopathology diagnosis is used as a standard criterion for determining the specialist assessment, algorithmic specificity, sensitivity and the area under the receiver operating characteristic curve (AUROC).

The concept of biotelemetry evolved to assess the physiological data of a person under normal circumstances without obstruction to the patient. It allows evaluation of risk factors influence the person health on their daily activities. Recent technology development enhances the features of biotelemetry as wireless applications which allows the physician to monitor the patient health remotely. Biotelemetry obtains great values in hospitals by continues monitoring process as it reduces the burden to physician regular checkups. ECG telemetry is one of the predominant biotelemetry application employed to monitor the heart rate and arrhythmias. Proposed research work focusses the key features of ECG telemetry and provides an internet of things (IoT) based application to monitor the patient health in an indoor and outdoor environment. Along with medical terms, data management parameters are analyzed in the experimental section to emphasize the proposed work performance.

In air handling units (AHUs), wide attention has been attracted by data-driven fault detection and diagnosis techniques as the need for high-level expert knowledge of the concerned system is eliminated. In AHUs, decision tree induction is performed by means of classification and regression tree algorithm which is a data-driven diagnostic strategy based on decision tree. Expert knowledge as well as testing data may be used for validation of fault diagnosis reliability with easy interpretation and understanding ability offered by the decision tree. The diagnostic strategy established and its interpretability are increased by incorporating a regression model and steady-state detector with the model. ASHRAE, Oak Ridge National Lab (ORNL), National Renewable Energy Lab (NREL), Pacific Northwest National Lab (PNNL) and Lawrence Berkeley National Lab (LBNL) datasets are used for validation of the proposed strategy. High average F-measure and improved diagnostic performance may be achieved with this strategy. There is a compliance between the expert knowledge and certain diagnostic rules generated in the decision tree as seen from the expert knowledge implemented diagnostic decision tree interpretation. Based on the interpretation, it is evident that certain diagnostic rules are valid only under specific operating conditions and some of the generated diagnostic rules are not reliable. Data driven models are used for emphasizing the significance of interpretability of fault diagnostic models.

The Computed Tomography (CT) image quality is determining by appropriate radiation dose in CT examination. Increases of the radiation dose become dangerous for our health such as induces of cancer, skin injuries, heritable mutations, reddening, burn the skins, etc. Therefore, the dose management study in the CT scanning procedure is one of the most important factors. This research article focuses on the use of the dose effectively in pediatric CT and cardiac CT scan procedures. Besides, the paper comprises dose hunt-down, auditing the scanner utilization, patient safety for the hospital association. This research article discusses radiation dose reduction techniques for effective dose in the view of future perspective in CT scan. This research article suggesting an appropriate technique to reduce the dose effectively in CT images during scanning. The effective dose test was conducted after reviews and ideas from future perspective designs.

We present a complete overview of routing protocols, routing algorithms, path planning, and cloud deployment for vehicle navigation in several fields of study in this article. In this article, we compare several approaches and algorithms with the goal of identifying the best feasible ones based on the type of application being utilized. In general, navigation of vehicles will be based on models and methods. Hence in this paper each characteristics are examined in detail and the research has been done accordingly. Under each characteristic, performance evaluation criteria are separately analysed. Questions are also provided for which the literature review serves as a form of discussion, according to the research challenge and criteria. For path planning, node-based as well as traditional algorithms are considered as the best choices. Similarly, the performance is significantly improved when using hybrid routing protocols and route planning methodologies that prefer graph based techniques. It has been observed that, a number of future research directions such as routing algorithm with queuing theory and path planning with critical link methods also serve the probable domains. This work is a concise comprehensive study of the various characteristics of a vehicle with respect to navigation. A comparison of techniques, algorithms and methods by using the standard performance criteria has also been elaborated.