Human error

Utilising Machine Learning (ML) models to predict dosimetric parameters in pencil beam scanning proton therapy presents a promising and practical approach. The study developed Artificial Neural Network (ANN) models to predict proton beam spot size and relative positional errors using 9000 proton spot data. The irradiation log files as input variables and corresponding scintillation detector measurements as the label values. The ANN models were developed to predict six variables: spot size in the x -axis, y -axis, major axis, minor axis, and relative positional errors in the x -axis and y -axis...

PURPOSE: To review all studies reporting the onset of white dot syndromes following COVID-19 vaccines. METHODS: Our protocol was registered prospectively on PROSPERO [registration number: CRD42023426012]. We searched five different databases including PubMed, Scopus, Web of Science, Google Scholar, and Science Direct up to May 2023. All the studies that reported the occurrence of white dot syndrome following COVID-19 vaccines were included. All statistical tests were conducted with a 95% confidence interval and a 5% error margin...

Brain segmentation from neonatal MRI images is a very challenging task due to large changes in the shape of cerebral structures and variations in signal intensities reflecting the gestational process. In this context, there is a clear need for segmentation techniques that are robust to variations in image contrast and to the spatial configuration of anatomical structures. In this work, we evaluate the potential of synthetic learning, a contrast-independent model trained using synthetic images generated from the ground truth labels of very few subjects...

This study addresses a crucial necessity in the field of noninvasive liver fibrosis diagnosis by introducing the concept of continuous shear wave elastography (C-SWE), utilizing an external vibration source and color Doppler imaging. However, an application of C-SWE to assess liver elasticity, a deep region within the human body, arises an issue of signal instability in the obtained data. To tackle this challenge, this work proposes a method involving the acquisition of multiple frames of datasets, which are subsequently compressed...

Human cells possess many different polymerase enzymes, which collaborate in conducting DNA replication and genome maintenance to ensure faithful duplication of genetic material. Each polymerase performs a specialized role, together providing a balance of accuracy and flexibility to the replication process. Perturbed replication increases the requirement for flexibility to ensure duplication of the entire genome. Flexibility is provided via the use of error-prone polymerases, which maintain the progression of challenged DNA replication at the expense of mutagenesis, an enabling characteristic of cancer...

BACKGROUND: Advanced prosthetic hands may embed nanosensors and microelectronics in their cosmetic skin. Heat influx may cause damage to these delicate structures. Protecting the integrity of the prosthetic hand becomes critical and necessary to ensure sustainable function. This study aims to mimic the sensorimotor control strategy of the human hand in perceiving nociceptive stimuli and triggering self-protective mechanisms and to investigate how similar neuromorphic mechanisms implemented in prosthetic hand can allow amputees to both volitionally release a hot object upon a nociceptive warning and achieve reinforced release via a bionic withdrawal reflex...

AIM: We aimed to investigate the efficiency and accuracy of an artificial intelligence (AI) algorithm for detecting interval cancers in a middle-income country's national screening program. MATERIAL AND METHODS: A total of 2,129,486 mammograms reported as BIRADS 1 and 2 were matched with the national cancer registry for interval cancers (IC). The IC group consisted of 442 cases, of which 36 were excluded due to having mammograms incompatible with the AI system. A control group of 446 women with two negative consequent mammograms was defined as time-proven normal and constituted the normal group...

In competitive interactions, humans have to flexibly update their beliefs about another person's intentions in order to adjust their own choice strategy, such as when believing that the other may exploit their cooperativeness. Here we investigate both the neural dynamics and the causal neural substrate of belief updating processes in humans. We used an adapted prisoner's dilemma task in which participants explicitly predicted the co-player's actions, which allowed us to quantify the prediction error between expected and actual behaviour...

BACKGROUND: Measuring spinal alignment with radiological parameters is essential in patients with spinal conditions likely to be treated surgically. These evaluations are not usually included in the radiological report. As a result, spinal surgeons commonly perform the measurement, which is time-consuming and subject to errors. We aim to develop a fully automated artificial intelligence tool to assist in measuring alignment parameters in whole-spine lateral radiograph (WSL X-rays). MATERIAL AND METHODS: We developed a tool called Vertebrai that automatically calculates the global spinal parameters (GSP): Pelvic incidence (PI), sacral slope (SS), pelvic tilt (PT), L1-L4 angle, L4-S1 lumbo-pelvic angle, T1 pelvic angle (TPA), sagittal vertical axis (SVA), cervical lordosis (CL), C1-C2 lordosis, lumbar lordosis (LL), mid-thoracic kyphosis (MTK), proximal thoracic kyphosis (PTK), global thoracic kyphosis (GTK), T1 slope (T1S), C2-C7 plummet (cSVA), spino-sacral angle (SSA), C7 tilt (C7T), global tilt (GT), spinopelvic tilt (T1SPi) and hip odontoid axis (OD-HA)...

BACKGROUND: Immersive virtual reality (IVR) as a research platform to study human behaviors is an emerging field and may be useful for studying self-care management, especially in the gap between formal healthcare recommendations and day-to-day living. Self-care activities, such as grocery shopping, can be challenging for people with chronic illness. We developed an IVR environment that simulates a real-life grocery store and conducted a usability study to demonstrate the safety and acceptability of IVR as an experimental environment...

BACKGROUND: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition software have been used to ease this burden, they have limitations in terms of accuracy and addressing provider-specific metrics...

Evaluation of human gait through smartphone-based pose estimation algorithms provides an attractive alternative to costly lab-bound instrumented assessment and offers a paradigm shift with real time gait capture for clinical assessment. Systems based on smart phones, such as OpenPose and BlazePose have demonstrated potential for virtual motion assessment but still lack the accuracy and repeatability standards required for clinical viability. Seq2seq architecture offers an alternative solution to conventional deep learning techniques for predicting joint kinematics during gait...

A highly efficient ratiometric electrochemiluminescence (ECL) immunoassay was explored by bidirectionally regulating the ECL intensity of two luminophors. The immunoassay was conducted in a split-type mode consisting of an ECL detection procedure and a sandwich immunoreaction. The ECL detection was executed using a dual-disk glassy carbon electrode modified with two potential-resolved luminophors (g-C3 N4 -Ag and Ru-MOF-Ag nanocomposites), and the sandwich immunoreaction using glucose oxidase (GOx)-modified SiO2 nanospheres as labels was carried out in a 96-well plate...

Elemental models of associative learning typically employ a common prediction-error term. Following a conditioning trial, they predict that the change in the strength of an association between a cue and an outcome is dependent upon how well the outcome was predicted. When multiple cues are present, they each contribute to that prediction. The same rule applies both to increases in associative strength during excitatory conditioning and the loss of associative strength during extinction. In five experiments using an allergy prediction task, we tested the involvement of a common error term in the extinction of causal learning...

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex...

Wearable inertial measurement units (IMUs) are used increasingly to estimate biomechanical exposures in lifting-lowering tasks. The objective of the study was to develop and evaluate predictive models for estimating relative hand loads and two other critical biomechanical exposures to gain a comprehensive understanding of work-related musculoskeletal disorders in lifting. We collected 12,480 lifting-lowering phases from 26 subjects (15 men and 11 women) performing manual lifting-lowering tasks with hand loads (0-22...

Malocclusion is a widespread oral health issue that adversely affects individuals' health and well-being. Currently, fixed orthodontics is considered the most efficient treatment for correcting malocclusion, with archwire bending playing a key role in orthodontic treatment. Traditionally, orthodontists manually performed archwire bending using various handheld pliers and other mechanical tools, requiring a significant amount of time, precision, and specialized training yet being unable to guarantee appliance accuracy...

Risk taking behavior is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula, and anterior cingulate have been implicated in risk-taking by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking...

Impulsive choices prioritize smaller, more immediate rewards over larger, delayed, or potentially uncertain rewards. Impulsive choices are a critical aspect of substance use disorders and maladaptive decision-making across the lifespan. Here, we sought to understand the neuronal underpinnings of expected reward and risk estimation on a trial-by-trial basis during impulsive choices. To do so, we acquired electrical recordings from the human brain while participants carried out a risky decision-making task designed to measure choice impulsivity...

Human Inborn Errors of Immunity (IEIs) encompass a clinically and genetically heterogeneous group of disorders, ranging from mild cases to severe, life-threatening types. Among these, Primary Immune Regulatory Disorders (PIRDs) constitute a subset of IEIs characterized by diverse clinical phenotypes, prominently featuring severe atopy, autoimmunity, lymphoproliferation, hyperinflammation, autoinflammation, and susceptibility to malignancies. According to the latest report from the International Union of Immunological Societies (IUIS), PIRDs arise from mutations in various genes including LYST, RAB27A, AP3B1, AP3D1, PRF1, UNC13D, STX11, STXBP2, FAAP24, SLC7A7, RASGRP1, CD70, CTPS1, RLTPR, ITK, MAGT1, PRKCD, TNFRSF9, SH2DIA, XIAP, CD27 (TNFRSF7), FAS (TNFRSF6), FASLG (TNFSF6), CASP10, CASP8, FADD, LRBA, STAT3, AIRE, ITCH, ZAP70, TPP2, JAK1, PEPD, FOXP3, IL2RA, CTLA4, BACH2, IL2RB, DEF6, FERMT1, IL10, IL10RA, IL10RB, NFAT5, TGFB1, and RIPK1 genes...