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Applying data science methodologies with artificial intelligence variant reinterpretation to map and estimate genetic disorder prevalence utilizing clinical data.

Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patient encounters. Genetic variants from all genetic testing resulting to a large pediatric healthcare system for a 5-year period were obtained and reinterpreted utilizing the previously validated Franklin© Artificial Intelligence (AI). Using PowerBI©, the data were further matched to patients in the electronic healthcare record to associate with demographic data to generate a variant data table and mapped by ZIP codes. Three thousand and sixty-five v…

Assessing the Quality of Patient Education Materials on Cardiac Catheterization From Artificial Intelligence Chatbots: An Observational Cross-Sectional Study.

Background Health literacy empowers patients to participate in their own healthcare. Personal health literacy is one's ability to find, understand, and use information/resources to make well-informed health decisions. Artificial intelligence (AI) has become a source for the acquisition of health-related information through large language model (LLM)-driven chatbots. Assessment of the readability and quality of health information produced by these chatbots has been the subject of numerous studies to date. This study seeks to assess the quality of patient education materials on cardiac catheteri…

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.

BACKGROUND: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale. METHODS: In this international, paired, non-inferiority, confirmator…

Artificial intelligence assisted patient blood and urine droplet pattern analysis for non-invasive and accurate diagnosis of bladder cancer.

Bladder cancer is one of the most common cancer types in the urinary system. Yet, current bladder cancer diagnosis and follow-up techniques … this gap, here we propose a quick, cheap, and reliable diagnostic method. Our approach relies on an artificial intelligence (AI) model to analyze droplet patterns of blood and urine samples obtained from patients and comparing them to cancer-free control subjects. The AI-assisted model in this study uses a deep neural network, a ResNet network, pre-trained on ImageNet da …

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. METHODS AND RESULTS: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-…

Review of Genetic and Artificial Intelligence approaches to improving Gestational Diabetes Mellitus Screening and Diagnosis in sub-Saharan Africa.

Background: Adverse outcomes from gestational diabetes mellitus (GDM) in the mother and newborn are well established. Genetic variants may predict GDM and Artificial Intelligence (AI) can potentially assist with improved screening and early identification in lower resource settings. There is limited information on genetic variants associated with GDM in sub-Saharan Africa and the implementation of AI in GDM screening in sub-Saharan Africa is largely unknown. Methods: We reviewed the literature on what is known about genetic predictors of GDM in sub-Saharan African women. We searched PubMed and…

An artificial intelligence-enabled Holter algorithm to identify patients with ventricular tachycardia by analysing their electrocardiogram during sinus rhythm.

AIMS: Ventricular tachycardia (VT) is a dangerous cardiac arrhythmia that can lead to sudden cardiac death. Early detection and management of VT is thus of high clinical importance. We hypothesize that it is possible to identify patients with VT during sinus rhythm by leveraging a continuous 24 h Holter electrocardiogram and artificial intelligence. METHODS AND RESULTS: We analysed a retrospective Holter data set from the Rambam Health Care Campus, Haifa, Israel, which included 1773 Holter recordings from 1570 non-VT patients and 52 recordings from 49 VT patients. Morphological and heart rate…

Artificial intelligence assisted preoperative planning and 3D-printing guiding frame for percutaneous screw reconstruction in periacetabular metastatic cancer patients.

BACKGROUND: The percutaneous screw reconstruction technique, known as the "Tripod Technique," has demonstrated favorable clinical outcomes in the management of metastatic periacetabular lesions, as evidenced by our prior investigations and corroborated by independent studies. Nevertheless, there is a steep learning curve in handling this technique, with possible complications such as intraarticular screw placement. METHODS: Preoperative pelvic CT scans were acquired before surgery and utilized for the guiding frame design. A convolutional neural network model was trained with annotated data t

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… Artificial Intelligence (AI)-assisted radiographic analysis is an innovative emerging technology that may potentially revolutionize the field of orthopedic surgery. … Artificial intelligence, especially machine learning-based radiography analysis, has gained immense popularity in recent years and has the potential to revolutionize the field of orthopedic surgery ( Oosterhoff and Doornberg, 2020 ; Chen et al., 2022 ). …

An Artificial Intelligence-Driven Approach for Automatic Evaluation of Right-to-Left Shunt Grades in Saline-Contrasted Transthoracic Echocardiography.

BACKGROUND: Intracardiac or pulmonary right-to-left shunt (RLS) is a common cardiac anomaly associated with an increased risk of neurological disorders, specifically cryptogenic stroke. Saline-contrasted transthoracic echocardiography (scTTE) is often used for RLS diagnosis. However, the identification of saline microbubbles in the left heart can be challenging for novice residents, potentially leading to a delay in diagnosis and treatment. In this study, we proposed an artificial intelligence (AI)-based algorithm designed to automatically detect microbubbles in scTTE images and evaluate right…

Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population.

BACKGROUND: Primary cervical cancer screening and treating precancerous lesions are effective ways to prevent cervical cancer. However, the coverage rates of human papillomavirus (HPV) vaccines and routine screening are low in most developing countries and even some developed countries. This study aimed to explore the benefit of an artificial intelligence-assisted cytology (AI) system in a screening program for a cervical cancer high-risk population in China. METHODS: A total of 1231 liquid-based cytology (LBC) slides from women who underwent colposcopy at the Chinese PLA General Hospital fro…

Artificial intelligence diagnostic model for multi-site fracture X-ray images of extremities based on deep convolutional neural networks.

BACKGROUND: The rapid and accurate diagnosis of fractures is crucial for timely treatment of trauma patients. Deep learning, one of the most widely used forms of artificial intelligence (AI), is now commonly employed in medical imaging for fracture detection. This study aimed to construct a deep learning model using big data to recognize multiple-fracture X-ray images of extremity bones. METHODS: Radiographic imaging data of extremities were retrospectively collected from five hospitals between January 2017 and September 2020. The total number of people finally included was 25,635 and the tot…

Comparison of three artificial intelligence algorithms for automatic cobb angle measurement using teaching data specific to three disease groups.

Spinal deformities, including adolescent idiopathic scoliosis (AIS) and adult spinal deformity (ASD), affect many patients. The measurement of the Cobb angle on coronal radiographs is essential for their diagnosis and treatment planning. To enhance the precision of Cobb angle measurements for both AIS and ASD, we developed three distinct artificial intelligence (AI) algorithms: AIS/ASD-trained AI (trained with both AIS and ASD cases); AIS-trained AI (trained solely on AIS cases); ASD-trained AI (trained solely on ASD cases). We used 1612 whole-spine radiographs, including 1029 AIS and 583 ASD …

A quality and readability comparison of artificial intelligence and popular health website education materials for common hand surgery procedures.

INTRODUCTION: ChatGPT and its application in producing patient education materials for orthopedic hand disorders has not been extensively studied. This study evaluated the quality and readability of educational information pertaining to common hand surgeries from patient education websites and information produced by ChatGPT. METHODS: Patient education information for four hand surgeries (carpal tunnel release, trigger finger release, Dupuytren's contracture, and ganglion cyst surgery) was extracted from ChatGPT (at a scientific and fourth-grade reading level), WebMD, and Mayo Clinic. In a bl

Artificial intelligence-based CT-free quantitative thyroid SPECT for thyrotoxicosis: study protocol of a multicentre, prospective, non-inferiority study.

INTRODUCTION: Technetium thyroid uptake (TcTU) measured by single-photon emission CT/CT (SPECT/CT) is an important diagnostic tool for the differential diagnosis of Graves' disease and destructive thyroiditis. Artificial intelligence (AI) may reduce CT-induced radiation exposure by substituting the role of CT in attenuation correction (AC) and thyroid segmentation, thus realising CT-free SPECT. This study aims to compare the diagnostic accuracy for the differential diagnosis of thyrotoxicosis between CT-free SPECT and SPECT/CT. METHODS AND ANALYSIS: The AI-based CT-free SPECT is a single-blin…

Evaluation of Vertical Level Differences Between Left and Right Vocal Folds Using Artificial Intelligence System in Excised Canine Larynx.

OBJECTIVES: This study aimed to establish an artificial intelligence (AI) system to classify vertical level differences between vocal folds during vocalization and to evaluate the accuracy of the classification. METHODS: We designed models with different depths between the right and left vocal folds using an excised canine larynx. Video files for the data set were obtained using a high-speed camera system and a color complementary metal oxide semiconductor camera with global shutter. The data sets were divided into training, validation, and testing. We used 20,000 images for building the mode…

From Outbreaks to Artificial Intelligence: A Comprehensive Review of Monkeypox Virus Epidemiology, Diagnosis, Treatment, Vaccination, and Deep Learning Applications.

Objectives: After the global impact of the COVID-19 pandemic, concerns over virus transmission have risen. A state of health emergency was d … idemiology, virology, clinical features, transmission routes, available drugs and vaccines, and new artificial intelligence (AI) applications in diagnosis and drug discovery. Results: MPOX virus is a 200-250-nm, double-stranded DNA (ds-DNA) virus that causes smallpox-like skin lesions. Tecovirimat is the primary drug for severe cases, especially in people with suppressed …

Artificial Intelligence Assisted Pharmacophore Design for Philadelphia Chromosome-Positive Leukemia with Gamma-Tocotrienol: A Toxicity Comparison Approach with Asciminib.

BCR-ABL1 is a fusion protein as a result of a unique chromosomal translocation (producing the so-called Philadelphia chromosome) that serves as a clinical biomarker primarily for chronic myeloid leukemia (CML); the Philadelphia chromosome also occurs, albeit rather rarely, in other types of leukemia. This fusion protein has proven itself to be a promising therapeutic target. Exploiting the natural vitamin E molecule gamma-tocotrienol as a BCR-ABL1 inhibitor with deep learning artificial intelligence (AI) drug design, this study aims to overcome the present toxicity that embodies the currently …

Enteroscopy versus Video Capsule Endoscopy for Automatic Diagnosis of Small Bowel Disorders-A Comparative Analysis of Artificial Intelligence Applications.

BACKGROUND: Small bowel disorders present a diagnostic challenge due to the limited accessibility of the small intestine. Accurate diagnosis is made with the aid of specific procedures, like capsule endoscopy or double-ballon enteroscopy, but they are not usually solicited and not widely accessible. This study aims to assess and compare the diagnostic effectiveness of enteroscopy and video capsule endoscopy (VCE) when combined with artificial intelligence (AI) algorithms for the automatic detection of small bowel diseases. MATERIALS AND METHODS: We performed an extensive literature search for…

Real-time artificial intelligence predicts adverse outcomes in acute pancreatitis in the emergency department: Comparison with clinical decision rule.

OBJECTIVE: Artificial intelligence (AI) prediction is increasingly used for decision making in health care, but its application for adverse outcomes in emergency department (ED) patients with acute pancreatitis (AP) is not well understood. This study aimed to clarify this aspect. METHODS: Data from 8274 ED patients with AP in three hospitals from 2009 to 2018 were analyzed. Demographic data, comorbidities, laboratory results, and adverse outcomes were included. Six algorithms were evaluated, and the one with the highest area under the curve (AUC) was implemented into the hospital information …

Comparison of artificial intelligence vs. junior dentists' diagnostic performance based on caries and periapical infection detection on panoramic images.

BACKGROUND: There is information missing in the literature about the comparison of dentists vs. artificial intelligence (AI) based on diagnostic capability. The aim of this study is to evaluate the diagnostic performance based on radiological diagnoses regarding caries and periapical infection detection by comparing AI software with junior dentists who have 1 or 2 years of experience, based on the valid determinations by specialist dentists. METHODS: In the initial stage of the study, 2 specialist dentists evaluated the presence of caries and periapical lesions on 500 digital panoramic radiog…