Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images.

Breast cancer is the most menacing cancer among all types of cancer in women around the globe. Early diagnosis is the only way to increase the treatment options which then decreases the death rate and increases the chance of survival in patients. However, it is a challenging task to differentiate abnormal breast tissues from normal tissues because of their structure and unclear boundaries.

Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniques.

Cervical cancer has become the third most common form of cancer in the in-universe, after the widespread breast cancer. Human papillomavirus risk of infection is linked to the majority of cancer cases. Preventive care, the most expensive way of fighting cancer, can protect about 37% of cancer cases.

Evaluation of Neuro Images for the Diagnosis of Alzheimer's Disease Using Deep Learning Neural Network.

Alzheimer's Disease (AD) is a progressive, neurodegenerative brain disease and is an incurable ailment. No drug exists for AD, but its progression can be delayed if the disorder is identified at its initial stage. Therefore, an early analysis of AD is of fundamental importance for patient care and efficient treatment.

Gulf Cooperation Council Clinical Trials in the Pursuit of Medications for COVID-19.

Tremendous changes have been witnessed in the post-COVID-19 world. Global efforts were initiated to reach a successful treatment for this emerging disease. These efforts have focused on developing vaccinations and/or finding therapeutic agents that can be used to combat the virus or reduce its accompanying symptoms.

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT.

The Industrial Internet of Things (IIoT) has led to the growth and expansion of various new opportunities in the new Industrial Transformation. There have been notable challenges regarding the security of data and challenges related to privacy when collecting real-time and automatic data while observing applications in the industry. This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT.

The Recent Technologies to Curb the Second-Wave of COVID-19 Pandemic.

Different epidemics, specially Coronavirus, have caused critical misfortunes in various fields like monetary deprivation, survival conditions, thus diminishing the overall individual fulfillment. Various worldwide associations and different hierarchies of government fraternity are endeavoring to offer the necessary assistance in eliminating the infection impacts but unfortunately standing up to the non-appearance of resources and expertise. In contrast to all other pandemics, Coronavirus has proven to exhibit numerous requirements such that curated appropriation and determination of innovations are required to deal with the vigorous undertakings, which include precaution, detection, and medication.

Blockchain technologies to mitigate COVID-19 challenges: A scoping review.

As public health strategists and policymakers explore different approaches to lessen the devastating effects of novel coronavirus disease (COVID-19), blockchain technology has emerged as a resource that can be utilized in numerous ways. Many blockchain technologies have been proposed or implemented during the COVID-19 pandemic; however, to the best of our knowledge, no comprehensive reviews have been conducted to uncover and summarise the main feature of these technologies. This study aims to explore proposed or implemented blockchain technologies used to mitigate the COVID-19 challenges as reported in the literature.

Correction to: Diagnosis and combating COVID-19 using wearable Oura smart ring with deep learning methods.

[This corrects the article DOI: 10.1007/s00779-021-01541-4.].

Diagnosis and combating COVID-19 using wearable Oura smart ring with deep learning methods.

Since the coronavirus (COVID-19) outbreak keeps on spreading all through the world, scientists have been crafting varied technologies mainly focusing on AI for an approach to acknowledge the difficulties of the epidemic. In this current worldwide emergency, the clinical business is searching for new advancements to screen and combat COVID-19 contamination. Strategies used by artificial intelligence can stretch screen the spread of the infection, distinguish highly infected patients, and be compelling in supervising the illness continuously.

A Comprehensive Overview of the COVID-19 Literature: Machine Learning-Based Bibliometric Analysis.

Background: Shortly after the emergence of COVID-19, researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, clinical manifestations, effects, treatments, and vaccinations. This led to a rapid increase in the number of COVID-19-related publications. Identifying trends and areas of interest using traditional review methods (eg, scoping and systematic reviews) for such a large domain area is challenging.

Artificial Intelligence in the Fight Against COVID-19: Scoping Review.

Background: In December 2019, COVID-19 broke out in Wuhan, China, leading to national and international disruptions in health care, business, education, transportation, and nearly every aspect of our daily lives. Artificial intelligence (AI) has been leveraged amid the COVID-19 pandemic; however, little is known about its use for supporting public health efforts.

Objective: This scoping review aims to explore how AI technology is being used during the COVID-19 pandemic, as reported in the literature.

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.

Background: The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world's health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19.

[Neurogenic paraosteopathy of the elbow: results of surgical arthrolysis (a retrospective study of 37 cases)].

Neurogenic paraosteoarthropathies are ectopic ossifications which develop near the joints. They are a process of neo-ectopic osteogenesis occurring after central or peripheral neurological lesions, in some types of comas (oxygen carbon intoxication, prolonged sedation) and following peripheral traumas including burns. They inolve almost exclusively the large proximal joints of the limbs.

[Mid-term results in the treatment of osteochondritis dissecans of the femoral condyles using osteochondral grafting (mosaic arthroplasty)].

Several surgical procedures, including mosaic arthroplasty, can be used to treat patients with cartilage loss in the femoral condyles. This study aims to assess mid-term clinical and radiological results as well as the main prognostics elements. We conducted a retrospective epidemiological study over a period of 15 years.

[Turrett's exostoses: about 35 casesk].

We conducted a retrospective study of 35 patients with subungual exostosis of the hallux, also known as Turrett's exostosis, in the Department of Orthopedics and Traumatology at the Senior Military Hospital of Instruction of Tunis over the period between 1995 and 2015. We here summarize the outcomes of patients treated for this disease. The average age of patients was 29 years, with a sex ratio of 1.

Simple statistical channel model for weak temperature-induced turbulence in underwater wireless optical communication systems.

In this Letter, we use laser beam intensity fluctuation measurements to model and describe the statistical properties of weak temperature-induced turbulence in underwater wireless optical communication (UWOC) channels. UWOC channels with temperature gradients are modeled by the generalized gamma distribution (GGD) with an excellent goodness of fit to the measured data under all channel conditions. Meanwhile, thermally uniform channels are perfectly described by the simple gamma distribution which is a special case of GGD.

[Results of the deltoid flap for surgery of rotator cuff tears].

Aim: Was to evaluate the results of deltoid flap for the treatment of massive rotator cuff tears.

Methods: This retrospective study included 20 shoulders in 20 patients with a painful massive, irreparable rotator cuff tears. The average patient age was 54 years.

[Stress fracture locations in military personnel].

Background: Physical exercise has beneficial effects on a number of physiologic systems, including the skeleton. However, combined with potential risk factors, unwise training practises may harm theses systems. A stress fracture represents one from of breakdown in the skeletal system.