Measurement of Cardiothoracic Ratio on Chest X-rays Using Artificial Intelligence-A Systematic Review and Meta-Analysis.

Chest X-rays (CXRs) are pivotal in clinical diagnostics, particularly in assessing cardiomegaly through the cardiothoracic ratio (CTR). This systematic review and meta-analysis evaluate the efficacy of artificial intelligence (AI) in automating CTR determination to enhance patient care and streamline diagnostic processes. They are concentrated on comparing the performance of AI models in determining the CTR against human assessments, identifying the most effective models for potential clinical implementation.

Accuracy of vestibular schwannoma segmentation using deep learning models - a systematic review & meta-analysis.

Unlabelled: Vestibular Schwannoma (VS) is a rare tumor with varied incidence rates, predominantly affecting the 60-69 age group. In the era of artificial intelligence (AI), deep learning (DL) algorithms show promise in automating diagnosis. However, a knowledge gap exists in the automated segmentation of VS using DL.

Deep Learning in Cardiothoracic Ratio Calculation and Cardiomegaly Detection.

: The purpose of this study is to evaluate the performance of our deep learning algorithm in calculating cardiothoracic ratio (CTR) and thus in the assessment of cardiomegaly or pericardial effusion occurrences on chest radiography (CXR). : From a database of 8000 CXRs, 13 folders with a comparable number of images were created. Then, 1020 images were chosen randomly, in proportion to the number of images in each folder.

Sharper vision, steady hands: can robots improve subretinal drug delivery? Systematic review.

Subretinal injection (SI) is a novel drug delivery method, directly to retina for treatment of various eye disease. However, manual injection requires surgical experience and precision due to physiological factors. Robots offer solution to this issue, by reducing hand tremor and increased accuracy.

Bridging the gap: robotic applications in cerebral aneurysms neurointerventions - a systematic review.

Cerebral aneurysm is a life-threatening condition, which requires high precision during the neurosurgical procedures. Increasing progress of evaluating modern devices in medicine have led to common usage of robotic systems in many fields, including cranial aneurysm operations. However, currently no systematic review describes up-to date knowledge of this topic.

Machine Meets Brain: A Systematic Review of Effectiveness of Robotically Performed Cerebral Angiography Interventions.

Background: Stroke is a leading cause of death in the United States, with significant economic and human costs. Early diagnosis and rapid treatment are critical for preventing stroke-related morbidity and mortality. However, accessibility to neurointerventional medical centers remains a challenge for many Americans, highlighting the need for innovative solutions to improve stroke management.

Mobile applications in radiology: own study based on polish data.

As the number of smartphones increases, so does the number of medical apps. Medical mobile applications are widely used in many medical fields by both patients and doctors. However, there are still few approved mobile applications that can be used in the diagnostic-therapeutic process and radiological apps are affected as well.

Multi-Label Classification of Chest X-ray Abnormalities Using Transfer Learning Techniques.

In recent years, deep neural networks have enabled countless innovations in the field of image classification. Encouraged by success in this field, researchers worldwide have demonstrated how to use Convolutional Neural Network techniques in medical imaging problems. In this article, the results were obtained through the use of the EfficientNet in the task of classifying 14 different diseases based on chest X-ray images coming from the NIH (National Institutes of Health) ChestX-ray14 dataset.

Chest X-ray Foreign Objects Detection Using Artificial Intelligence.

Diagnostic imaging has become an integral part of the healthcare system. In recent years, scientists around the world have been working on artificial intelligence-based tools that help in achieving better and faster diagnoses. Their accuracy is crucial for successful treatment, especially for imaging diagnostics.

What Is Machine Learning, Artificial Neural Networks and Deep Learning?-Examples of Practical Applications in Medicine.

Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all topics that fall under the heading of artificial intelligence (AI) and have gained popularity in recent years. ML involves the application of algorithms to automate decision-making processes using models that have not been manually programmed but have been trained on data. ANNs that are a part of ML aim to simulate the structure and function of the human brain.

Usability of Mobile Solutions Intended for Diagnostic Images-A Systematic Review.

Despite the growing popularity of mobile devices, they still have not found widespread use in medicine. This is due to the procedures in a given place, differences in the availability of mobile devices between individual institutions or lack of appropriate legal regulations and accreditation by relevant institutions. Numerous studies have been conducted and compared the usability of mobile solutions designed for diagnostic images evaluation on various mobile devices and applications with classic stationary descriptive stations.

Medical robots in cardiac surgery - application and perspectives.

Medical robots offer new standards and opportunities for treatment. This paper presents a review of the literature and market information on the current situation and future perspectives for the applications of robots in cardiac surgery. Currently in the United States, only 10% of thoracic surgical procedures are conducted using robots, while globally this value remains below 1%.

Total mesorectal excision using a soft and flexible robotic arm: a feasibility study in cadaver models.

Background: Sponsored by the European Commission, the FP7 STIFF-FLOP project aimed at developing a STIFFness controllable Flexible and Learn-able manipulator for surgical operations, in order to overcome the current limitations of rigid-link robotic technology. Herein, we describe the first cadaveric series of total mesorectal excision (TME) using a soft and flexible robotic arm for optic vision in a cadaver model.

Methods: TME assisted by the STIFF-FLOP robotic optics was successfully performed in two embalmed male human cadavers.

State of the art in medical robotics in Poland: development of the Robin Heart and other robots.

The first Polish project in medical robotics began in 2000. Now, a decade later, the Robin Heart surgical telemanipulator has the potential to become widely used in many branches of surgery. The original robot and mechatronic tools have successfully completed the required laboratory tests and animal studies.

Norwood with right ventricle-to-pulmonary artery conduit is more effective than Norwood with Blalock-Taussig shunt for hypoplastic left heart syndrome: mathematic modeling of hemodynamics.

Objective: The introduction of right ventricle to pulmonary artery (RV-PA) conduit in the Norwood procedure for hypoplastic left heart syndrome resulted in a higher survival rate in many centers. A higher diastolic aortic pressure and a higher mean coronary perfusion pressure were suggested as the hemodynamic advantage of this source of pulmonary blood flow. The main objective of this study was the comparison of two models of Norwood physiology with different types of pulmonary blood flow sources and their hemodynamics.

The influence of physical and chemical agents on photooxidation of porcine pericardial collagen.

Photooxidation is a method of tissue fixation resulting in protein crosslinking due to illumination in the presence of a dye. The aim of the study was to evaluate the impact of dyes, photooxidation time and the type of applied light on the porcine pericardial collagen crosslinking. The collagen modifications were evaluated on the basis of pericardial sensitivity to pepsin digestion.

[Methods of collagenous tissue fixation in the preparation of bioprostheses].

The use of biological materials in construction of bioprostheses requires the application of different chemical or physical procedures of fixation increasing bioprostheses resistance to enzymatic or chemical degradation and reducing their antigenicity. Methods typically concentrate on creating additional intra- and intermolecular chemical bonds between collagen molecules. This review focuses on the various methods of stabilization of collagenous tissues including chemical fixatives and physical agents.