Stud Health Technol Inform
November 2024
This paper proposes to create an Robotic Process Automation style application that can digitalize and extract data from handwritten medical forms. The RPA robot uses OpenAI ChatGPT4o model to extract handwritten medical data and transform it into typed data. The handwritten data is transcribed correctly at a rate of 100%.
View Article and Find Full Text PDFThe existing pill dispenser systems help elderly people to improve their quality of life, and medication adherence. But these systems lack interactive capabilities with caregivers, a crucial element in comprehensive home care management. The suggested CareConnect aims to bridge this gap by introducing a Telecare extension that not only manages medication adherence but also facilitates interaction between the patient and their caregivers.
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August 2024
In recent years, artificial intelligence, and machine learning (ML) models have advanced significantly, offering transformative solutions across diverse sectors. Emotion recognition in speech has particularly benefited from ML techniques, revolutionizing its accuracy and applicability. This article proposes a method for emotion detection in Romanian speech analysis by combining two distinct approaches: semantic analysis using GPT Transformer and acoustic analysis using openSMILE.
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October 2023
When it comes to health, a very widespread problem nowadays is mental health, where almost 18% of the world's population suffers from certain mental illnesses. Artificial intelligence (AI) is a concept that evolves strongly and is expected in the near future to bring improvements and help to humans in various fields. The field of mental health is not excluded, so AI can help in the performance of medical services, either by helping the medical staff or patients.
View Article and Find Full Text PDFThis paper describes the latest development in the classification stage of our Speech Sound Disorder (SSD) Screening algorithm and presents the results achieved by using two classifier models: the Classification and Regression Tree (CART)-based model versus the Single Decision Hyperplane-based Linear Support Vector Machine (SVM) model. For every single speech sound in medial position, 10 features extracted from the audio samples along with an 11th feature representing the validation of the (mis)pronunciation by the Speech Language Pathologist (SLP) were fed into the 2 classifiers to compare and discuss their performance. The accuracy achieved by the two classifiers on a data test size of 30% of the analyzed samples was 98.
View Article and Find Full Text PDFStud Health Technol Inform
October 2023
This paper proposes to create an RPA(robotic process automation) based software robot that can digitalize and extract data from handwritten medical forms. The RPA robot uses a taxonomy that is specific for the medical form and associates the extracted data with the taxonomy. This is accomplished using UiPath studio to create the robot, Google Cloud Vision OCR(optical character recognition) to create the DOM (digital object model) file and UiPath machine learning (ML) API to extract the data from the medical form.
View Article and Find Full Text PDFThis paper presents a Support-Vector Machine (SVM) based method of classification of cross-correlated phoneme segments as part of the development of an automated Speech Sound Disorder (SSD) Screening tool. The pre-processing stage of the algorithm uses cross-correlation to segment the target phoneme and extracts data from the new homogeneously trimmed audio samples. Such data is then fed into the SVM-based classification script which currently achieves an accuracy of 97.
View Article and Find Full Text PDFWith the increase in computing power and the development of numerous technological devices that facilitate remote work, the involvement of artificial intelligence in medicine has seen a significant increase to help the doctor make decisions and intervene in the medical process and telemedicine. In this paper, we gave an overview of the practical involvement of artificial intelligence through different support systems used in primary medicine or telemedicine and also identified the possibilities and opportunities for the development of new support systems for family medicine. Thus, we identified systems used for primary diagnosis, diagnosis of hypertension, early detection of heart abnormalities, detection of diabetes, support in the prescription process, helping clinicians in the daily workflow by providing certain answers to questions, treatment guidance, determining patient priority for treatment for SARS-CoV-2 infection or early detection of disease, support of artificial ventilation in medical emergency centers, remote support for treatments and medication.
View Article and Find Full Text PDFThe goal of this paper is to present a word-final target phoneme automated segmentation method based on cross-correlation coefficients computed between a reference sound wave and a sample sound wave. Most existing Speech Sound Disorder (SSD) Screening solutions require human intervention to a greater or lesser extent and use segmentation methods based on hard-coded time frames. Moreover, existing solutions extract features from the frequency domain, which entails large amounts of computational power to the detriment of real-time feedback.
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June 2020
This paper presents an audio file segmentation method in an attempt to mitigate the issue of variable durations of the same utterance by different individuals, e.g.: Speech-Language Pathologist (SLP) and dyslalic subjects.
View Article and Find Full Text PDFLow back pain is one of the most common physical symptom and is frequently related with an abnormal body posture. It may be caused by poor upper body and limb coordination; repetitive lifting of heavy objects or poor working are ergonomics. This study analysis the consequence of repetitive heavy lifting on the normal standing posture of factory workers.
View Article and Find Full Text PDFThis paper's objective is to present a proposed solution of Computer-based Speech Therapy System (CBST) for dyslalia screening. The problem of Speech Sound Disorders (SSD) is enunciated, and a brief presentation of several general CBST solutions is made. An Entropy-based method is proposed and the current state of advancement in the development and experimental validation of this solution is presented and discussed.
View Article and Find Full Text PDFThis paper makes a brief review of several database structures of Computer-Based Speech Therapy (CBST) systems and solutions and describes the screening method, an experimental study conducted to validate the screening algorithm and a database structure for the Information Entropy-Based Sound Speech Disorder (SSD) Screening System aimed at by our research project. The final part briefly presents the essential design criteria and further development.
View Article and Find Full Text PDFThis paper proposes the evaluation of the Oswestry Disability Index (ODI) using a fuzzy inference system. The ODI is used to evaluate the impact of the low back pain on the patient's quality of life. The patient grades from 0 to 5 a number of 10 questions regarding usual daily activities.
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November 2018
This paper reviews several architectures of Computer-Based Speech Therapy (CBST) systems and solutions and describes an architecture for an Entropy-Based Sound Speech Disorder (SSD) Screening System aimed at by our research project. The proposed architecture and data flow scenario aim to provide a fully-automated Entropy-based SSD Screening System, to be connected with CBSTs and to be used as a research infrastructure for further refinement of the objectives of our research project.
View Article and Find Full Text PDFThis paper suggests the usage of the Microsoft Kinect to detect the onset of the scoliosis at high school students due to incorrect sitting positions. The measurement is done by measuring the overall posture in orthostatic position using the Microsoft Kinect. During the measuring process several key points of the human body are tracked like the hips and shoulders to form the postural data.
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May 2017
This paper proposes a virtual patient (VP) for the medical rehabilitation domain using the digital representation of the real life patient's matchstick skeleton. This virtual patient is used to analyze and track the recovery of the orthopedic patient with malicious posture problems. The creation of the digital patient was realized using a markerless depth camera, the Microsoft Kinect.
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May 2017
This research presents the results of evaluating multiple free, open-source engines on matching ICD-10 diagnostic codes via full-text searches. The study investigates what it takes to get an accurate match when searching for a specific diagnostic code. For each code the evaluation starts by extracting the words that make up its text and continues with building full-text search queries from the combinations of these words.
View Article and Find Full Text PDFStud Health Technol Inform
November 2016
For more than a decade, the eHealth initiative has been a government concern of many countries. In an Electronic Health Record (EHR) System, there is a need for sharing the data with a group of specialists simultaneously. Collaborative platforms alone are just a part of a solution, while a collaborative platform with parallel editing capabilities and with synchronized data streaming are stringently needed.
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November 2016
This paper presents an intelligent Kinect and fuzzy inference system based e-rehabilitation system. The Kinect can detect the posture and motion of the patients while the fuzzy inference system can interpret the acquired data on the cognitive level. The system is capable to assess the initial posture and motion ranges of 20 joints.
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November 2016
Medical terminology appears in the natural language in multiple forms: canonical, derived or inflected form. This research presents an analysis of the form in which medical terminology appears in Romanian and English language. The sources of medical language used for the study are web pages presenting medical information for patients and other lay users.
View Article and Find Full Text PDFeduCRATE is a complex project proposal which aims to develop a virtual learning environment offering interactive digital content through original and integrated solutions using cloud computing, complex multimedia systems in virtual space and personalized design with avatars. Compared to existing similar products the project brings the novelty of using languages for medical guides in order to ensure a maximum of flexibility. The Virtual Hospital simulations will create interactive clinical scenarios for which students will find solutions for positive diagnosis and therapeutic management.
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April 2015
The paper presents a fuzzy inference system based prediction with the role to determine the appropriate action for patients that presents lower back pain. If not treated correctly lower back pain can degenerate in various diseases. The system infers three possible actions: (1) spinal cord surgery, (2) medication combined with exercises and (3) no action needed.
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April 2015
Using data mining in collaboration with Clinical Decision Support Systems adds new knowledge as support for medical diagnosis. The current work presents a tool which translates data mining rules supporting generation of medical advices to Arden Syntax formalism. The developed system was tested with data related to 2326 births that took place in 2010 at the Bega Obstetrics - Gynaecology Hospital, Timişoara.
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January 2013
Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record).
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