Preventive Care

[Technological Innovations in Pulmonology - Examples from Diagnostics and Therapy].

A significant proportion of the current technological developments in pneumology originate from the various areas of information technology. The spectrum ranges from smartphone apps to be used in daily life or in patient care to the use of artificial intelligence in screening and early detection of diseases. The diagnostic accuracy of apps for symptom analysis is currently very limited. Research p...

An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm.

The herpesvirus, polyomavirus, papillomavirus, and retrovirus families are associated with breast cancer. More effort is needed to assess the role of these viruses in the detection and diagnosis of breast cancer cases in women. The aim of this paper is to propose an efficient segmentation and classification system in the Mammography Image Analysis Society (MIAS) images of medical images. Segmentat...

Polyp Segmentation with Fully Convolutional Deep Neural Networks-Extended Evaluation Study.

Analysis of colonoscopy images plays a significant role in early detection of colorectal cancer. Automated tissue segmentation can be useful for two o...

Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm.

BACKGROUND: Fecal examination is an important component of routine companion animal wellness exams. Sensitivity and specificity of fecal examinations,...

Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning.

BACKGROUND: Diabetic retinopathy (DR), the most common cause of vision loss, is caused by damage to the small blood vessels in the retina. If untreate...

COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning.

To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease cau...

Diabetic Retinopathy Screening with Automated Retinal Image Analysis in a Primary Care Setting Improves Adherence to Ophthalmic Care.

PURPOSE: Retinal screening examinations can prevent vision loss resulting from diabetes but are costly and highly underused. We hypothesized that arti...

Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study.

BACKGROUND AND AIMS: Up to 30% of adenomas might be missed during screening colonoscopy-these could be polyps that appear on-screen but are not recogn...

Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.

Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemic COVID-19. Early symptoms overlap with other comm...

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer.

Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by tra...

A preliminary evaluation of still face images by deep learning: A potential screening test for childhood developmental disabilities.

Most developmental disorders are defined by their clinical symptoms and many disorders share common features. The main objective of this research is t...

Regulatory considerations for artificial intelligence technologies in GI endoscopy.

Artificial intelligence (AI) technologies in clinical medicine have become the subject of intensive investigative efforts and popular attention. In do...

An innovative method for screening and evaluating the degree of diabetic retinopathy and drug treatment based on artificial intelligence algorithms.

Current methods of evaluating the degree of diabetic retinopathy are highly subjective and have no quantitative standard. To objectively evaluate the ...

Automated computer-assisted detection system for cerebral aneurysms in time-of-flight magnetic resonance angiography using fully convolutional network.

BACKGROUND: As the rupture of cerebral aneurysm may lead to fatal results, early detection of unruptured aneurysms may save lives. At present, the con...

Polyp detection algorithm can detect small polyps: Ex vivo reading test compared with endoscopists.

BACKGROUND AND STUDY AIMS: Small polyps are occasionally missed during colonoscopy. This study was conducted to validate the diagnostic performance of...

Improvement of oral cancer screening quality and reach: The promise of artificial intelligence.

Oral cancer is easily detectable by physical (self) examination. However, many cases of oral cancer are detected late, which causes unnecessary morbid...

A high-throughput system combining microfluidic hydrogel droplets with deep learning for screening the antisolvent-crystallization conditions of active pharmaceutical ingredients.

Crystallization of active pharmaceutical ingredients (APIs) is a crucial process in the pharmaceutical industry due to its great impact in drug effica...

A machine learning approach to risk assessment for alcohol withdrawal syndrome.

At present, risk assessment for alcohol withdrawal syndrome relies on clinical judgment. Our aim was to develop accurate machine learning tools to pre...

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

BACKGROUND & AIMS: One-fourth of colorectal neoplasias are missed during screening colonoscopies; these can develop into colorectal cancer (CRC). Deep...

The impact of deep convolutional neural network-based artificial intelligence on colonoscopy outcomes: A systematic review with meta-analysis.

BACKGROUND AND AIM: The utility of artificial intelligence (AI) in colonoscopy has gained popularity in current times. Recent trials have evaluated th...