Incorporating artificial intelligence in portable infrared thermal imaging for the diagnosis and staging of nonalcoholic fatty liver disease.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is one of the most prevalent chronic liver diseases worldwide. Thermal imaging combined with advanced image-processing and machine learning analysis accurately classified disease status in a study on mice; this study aimed to develop this tool for humans. This prospective study included 46 patients who underwent liver biopsy.

Significant reduction of the culturing time required for bacterial identification and antibiotic susceptibility determination by infrared spectroscopy.

Rapid testing of bacteria for antibiotic susceptibility is essential for effective treatment and curbing the emergence of multidrug-resistant bacteria. The misuse of antibiotics, coupled with the time-consuming classical testing methods, intensifies the threat of antibiotic resistance, a major global health concern. In this study, employing infrared spectroscopy-based machine learning techniques, we significantly shortened the time required for susceptibility testing to 10 hours, a significant improvement from the 24 hours in our previous studies as well as the conventional methods that typically take at least 48 hours.

Conductive Peptide-Based MXene Hydrogel as a Piezoresistive Sensor.

Wearable pressure sensors have become increasingly popular for personal healthcare and motion detection applications due to recent advances in materials science and functional nanomaterials. In this study, a novel composite hydrogel is presented as a sensitive piezoresistive sensor that can be utilized for various biomedical applications, such as wearable skin patches and integrated artificial skin that can measure pulse and blood pressure, as well as monitor sound as a self-powered microphone. The hydrogel is composed of self-assembled short peptides containing aromatic, positively- or negatively charged amino acids combined with 2D TiCT MXene nanosheets.

Infrared spectroscopy-based machine learning algorithms for rapid detection of Klebsiella pneumoniae isolated directly from patients' urine and determining its susceptibility to antibiotics.

Among the most prevalent and detrimental bacteria causing urinary tract infections (UTIs) is Klebsiella (K.) pneumoniae. A rapid determination of its antibiotic susceptibility can enhance patient treatment and mitigate the spread of resistant strains.

Classification of hand and wrist movements via surface electromyogram using the random convolutional kernels transform.

Prosthetic devices are vital for enhancing personal autonomy and the quality of life for amputees. However, the rejection rate for electric upper-limb prostheses remains high at around 30%, often due to issues like functionality, control, reliability, and cost. Thus, developing reliable, robust, and cost-effective human-machine interfaces is crucial for user acceptance.

Smartphone-based detection of COVID-19 and associated pneumonia using thermal imaging and a transfer learning algorithm.

COVID-19-related pneumonia is typically diagnosed using chest x-ray or computed tomography images. However, these techniques can only be used in hospitals. In contrast, thermal cameras are portable, inexpensive devices that can be connected to smartphones.

Enhanced Transmission at the Zeroth-Order Mode of a Terahertz Fabry-Perot Cavity.

A planar Fabry-Perot cavity with intermirror spacing of ≪ λ is explored for its "zero-order mode" terahertz transmission. The enhanced transmission observed as → 0 indicates that such cavities satisfy the resonance conditions across a broad terahertz bandwidth. The experimental signatures from this elusive, "technically challenging" regime are evidenced using time-domain terahertz spectroscopy and are complemented by numerical calculations.

Mechanical impact of epiretinal membranes on the retina utilizing finite element analysis.

Background And Objective: Epiretinal membrane (ERM) is a transparent membrane that forms on the surface of the neurosensory retina, causing tangential traction on the retinal surface, which may contribute to cell proliferation and contraction. Epiretinal membranes (ERMs) may be asymptomatic in some patients, while in others the membranes can progress, resulting in macular thickening and macular traction, thus distorting and inducing loss of central visual function and metamorphopsia. Currently, treatment options include follow-up or pars plana vitrectomy with an ERM peel, aiming to relieve the macular traction and improve vision and metamorphopsia.

Monitoring the efficacy of antibiotic therapy in febrile pediatric oncology patients with bacteremia using infrared spectroscopy of white blood cells-based machine learning.

Bacteremia refers to the presence of bacteria in the bloodstream, which can lead to a serious and potentially life-threatening condition. In oncology patients, individuals undergoing cancer treatment have a higher risk of developing bacteremia due to a weakened immune system resulting from the disease itself or the treatments they receive. Prompt and accurate detection of bacterial infections and monitoring the effectiveness of antibiotic therapy are essential for enhancing patient outcomes and preventing the development and dissemination of multidrug-resistant bacteria.

Programmable comprehensive controller for multi-color 3D confocal spinning-disk image scanning microscope.

This paper introduces a compact, portable, and highly accurate triggering control system for a 3D confocal spinning-disk image scanning microscope (CSD-ISM). Building upon on our previously published research, we expanded the hardware of the controller and synchronized it with a sub-micron translator which scans the object in the z-direction. As well as expanding the hardware, the software also was extended from previously published work similarly as it is stated for hardware while allowing full control over the 3D movement.

Thermographic Changes following Short-Term High-Intensity Anaerobic Exercise.

Current studies report thermographic changes following aerobic or resistance exercise but not short, vigorous anaerobic exercise. Therefore, we investigated body surface temperature changes using thermal imaging following a short session of anaerobic exercise. We studied three different regions of interest (ROIs): the legs, chest, and forehead.

Alert-Grouping: Smart Personalization of Monitoring System Thresholds to Help Healthcare Teams Struggle with Alarm Fatigue in Intensive Care.

In Intensive Care Units (ICUs), patients are monitored using various devices that generate alerts when specific metrics, such as heart rate and oxygen saturation, exceed predetermined thresholds. However, these alerts can be inaccurate and lead to alert fatigue, resulting in errors and inaccurate diagnoses. We propose Alert grouping, a "Smart Personalization of Monitoring System Thresholds to Help Healthcare Teams Struggle Alarm Fatigue in Intensive Care" model.

Quick Detection of and in Patients' Urine and Assessing Their Antibiotic Susceptibility Using Infrared Spectroscopy and Machine Learning.

Bacterial resistance to antibiotics is a primary global healthcare concern as it hampers the effectiveness of commonly used antibiotics used to treat infectious diseases. The development of bacterial resistance continues to escalate over time. Rapid identification of the infecting bacterium and determination of its antibiotic susceptibility are crucial for optimal treatment and can save lives in many cases.

Morphological features of the photoplethysmographic signal: a new approach to characterize the microcirculatory response to photobiomodulation.

Advanced analysis of the morphological features of the photoplethysmographic (PPG) waveform may provide greater understanding of mechanisms of action of photobiomodulation (PBM). Photobiomodulation is a non-ionizing, red to near-infrared irradiation shown to induce peripheral vasodilatation, promote wound healing, and reduce pain. Using laser Doppler flowmetry combined with thermal imaging we found previously in a clinical study that PBM stimulates microcirculatory blood flow and that baseline palm skin temperature determines, at least in part, why some individuals respond favorably to PBM while others do not.

Inducing Mechanical Stimuli to Tissues Grown on a Magnetic Gel Allows Deconvoluting the Forces Leading to Traumatic Brain Injury.

Traumatic brain injury (TBI), which is characterized by damage to the brain resulting from a sudden traumatic event, is a major cause of death and disability worldwide. It has short- and long-term effects, including neuroinflammation, cognitive deficits, and depression. TBI consists of multiple steps that may sometimes have opposing effects or mechanisms, making it challenging to investigate and translate new knowledge into effective therapies.

Early Detection of Pre-Cancerous and Cancerous Cells Using Raman Spectroscopy-Based Machine Learning.

Cancer is the most common and fatal disease around the globe, with an estimated 19 million newly diagnosed patients and approximately 10 million deaths annually. Patients with cancer struggle daily due to difficult treatments, pain, and financial and social difficulties. Detecting the disease in its early stages is critical in increasing the likelihood of recovery and reducing the financial burden on the patient and society.

A Platform for Assessing Cellular Contractile Function Based on Magnetic Manipulation of Magnetoresponsive Hydrogel Films.

Despite significant advancements in in vitro cardiac modeling approaches, researchers still lack the capacity to obtain in vitro measurements of a key indicator of cardiac function: contractility, or stroke volume under specific loading conditions-defined as the pressures to which the heart is subjected prior to and during contraction. This work puts forward a platform that creates this capability, by providing a means of dynamically controlling loading conditions in vitro. This dynamic tissue loading platform consists of a thin magnetoresponsive hydrogel cantilever on which 2D engineered myocardial tissue is cultured.

Small Files Problem Resolution via Hierarchical Clustering Algorithm.

The Small Files Problem in Hadoop Distributed File System (HDFS) is an ongoing challenge that has not yet been solved. However, various approaches have been developed to tackle the obstacles this problem creates. Properly managing the size of blocks in a file system is essential as it saves memory and computing time and may reduce bottlenecks.

Natural history of changes in knee skin temperature following total knee arthroplasty: a systematic review and meta-analysis.

Patients undergoing total-knee arthroplasty (TKA) have transient increases in anterior knee skin temperature (ST) that subside as recovery progresses-except in cases of systemic or local prosthetic joint infections (PJI). This meta-analysis was designed to quantify the changes in knee ST following TKA in patients with uncomplicated recovery as a prerequisite for assessing the usefulness of thermal imaging for diagnosis of PJI. This meta-analysis (PROSPERO-CRD42021269864) was performed according to PRISMA guidelines.

Deep Learning Solution of the Eigenvalue Problem for Differential Operators.

Solving the eigenvalue problem for differential operators is a common problem in many scientific fields. Classical numerical methods rely on intricate domain discretization and yield nonanalytic or nonsmooth approximations. We introduce a novel neural network-based solver for the eigenvalue problem of differential self-adjoint operators, where the eigenpairs are learned in an unsupervised end-to-end fashion.

Portable low-cost and highly accurate programmable triggering controller for confocal spinning disk image scanning microscope.

This work presents a very low-cost and highly accurate alternative way of implementing triggering control for a confocal spinning-disk image scanning microscope (CSD-ISM). Instead of using the previously reported hig-cost field programmable gate array (FPGA), that connects to a computer by an internal PCIe bus, we implemented the controller using a simple, low-cost real-time digital signal controller (DSC) development kit that connects to a computer via an external USB channel. The overall time resolution of the controller is better than 10 nanoseconds.

Detection of extended-spectrum β-lactamase-producing bacteria isolated directly from urine by infrared spectroscopy and machine learning.

Resistant bacteria have become one of the leading health threats in the last decades. Extended-spectrum β-lactamase (ESBL) producing bacteria, including Escherichia (E.) coli and Klebsiella (K.

Automatized Detection of Crohn's Disease in Intestinal Ultrasound Using Convolutional Neural Network.

Introduction: The use of intestinal ultrasound (IUS) for the diagnosis and follow-up of inflammatory bowel disease is steadily growing. Although access to educational platforms of IUS is feasible, novice ultrasound operators lack experience in performing and interpreting IUS. An artificial intelligence (AI)-based operator supporting system that automatically detects bowel wall inflammation may simplify the use of IUS by less experienced operators.

Instant detection of extended-spectrum β-lactamase-producing bacteria from the urine of patients using infrared spectroscopy combined with machine learning.

Antibiotics are considered the most effective treatment against bacterial infections. However, most bacteria have already developed resistance to a broad spectrum of commonly used antibiotics, mainly due to their uncontrolled use. Extended-spectrum beta-lactamase (ESBL)-producing bacteria are an essential class of multidrug-resistant (MDR) bacteria.