A5005580741- Autism Spectrum Disorder Research
- Behavioral and Psychological Studies
- Sepsis Diagnosis and Treatment
- Child Nutrition and Feeding Issues
- Data Stream Mining Techniques
- Respiratory Support and Mechanisms
- Topic Modeling
- Family and Disability Support Research
- Machine Learning in Healthcare
- Machine Learning and Data Classification
- Healthcare Technology and Patient Monitoring
- Healthcare Systems and Public Health
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Anomaly Detection Techniques and Applications
- Non-Invasive Vital Sign Monitoring
- Text Readability and Simplification
- Artificial Intelligence in Healthcare and Education
- Natural Language Processing Techniques
- Attention Deficit Hyperactivity Disorder
- Domain Adaptation and Few-Shot Learning
- Health Promotion and Cardiovascular Prevention
- Acute Myocardial Infarction Research
- Biomedical Text Mining and Ontologies
- Dementia and Cognitive Impairment Research
Dascena (United States)
2022
Guru Teg Bahadur Hospital
2014
Guru Gobind Singh Indraprastha University
2014
LLMs can accomplish specialized medical knowledge tasks, however, equitable access is hindered by the extensive fine-tuning, data requirement, and limited to proprietary models. Open-source (OS) show performance improvements provide transparency compliance required in healthcare. We present OpenMedLM, a prompting platform delivering state-of-the-art (SOTA) for OS on benchmarks. evaluated foundation (7B-70B) benchmarks (MedQA, MedMCQA, PubMedQA, MMLU medical-subset) selected Yi34B developing...
Mild cognitive impairment (MCI) is decline that can indicate future risk of Alzheimer’s disease (AD). We developed and validated a machine learning algorithm (MLA), based on gradient-boosted tree ensemble method, to analyze phenotypic data for individuals 55–88 years old (n = 493) diagnosed with MCI. Data were analyzed within multiple prediction windows averaged predict progression AD 24–48 months. The MLA outperformed the mini-mental state examination (MMSE) three comparison models at all...
Acute respiratory distress syndrome (ARDS) is a condition that often considered to have broad and subjective diagnostic criteria associated with significant mortality morbidity. Early accurate prediction of ARDS related conditions such as hypoxemia sepsis could allow timely administration therapies, leading improved patient outcomes.The aim this study perform an exploration how multilabel classification in the clinical setting can take advantage underlying dependencies between improve early...
Background/Objective: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by lifelong impacts on functional social and daily living skills, restricted, repetitive behaviors (RRBs). Applied behavior analysis (ABA), the gold-standard treatment for ASD, has been extensively validated. ABA access hindered limited availability of qualified professionals logistical financial barriers. Scientifically validated, parent-led can fill accessibility gap overcoming This...
Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges be mitigated early identification. However, diagnostic criteria has changed from DSM-IV to DSM-5, which make diagnosing a disorder complex. We evaluated machine learning classify individuals having one of three disorders under DSM-IV, or non-spectrum.
Objective This study examines the implementation of a hybrid applied behavioral analysis (ABA) treatment model to determine its impact on autism spectrum disorder (ASD) patient outcomes. Methods Retrospective data were collected for 25 pediatric patients measure progress before and after ABA under which therapists consistently captured session notes electronically regarding goals progress. was streamlined consistent delivery, with improved software utilization tracking scheduling Eleven...
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Type 2 diabetes (T2D) is a global health concern with increasing prevalence. Comorbid hypothyroidism (HT) exacerbates kidney, cardiac, neurological and other complications of T2D; these risks can be mitigated pharmacologically upon detecting HT. The current HT standard care (SOC) screening in T2D infrequent, delaying diagnosis treatment. We present first-to-date machine learning algorithm (MLA) clinical decision tool to classify patients as low vs. high risk for developing comorbid the MLA...
Autism spectrum disorder (ASD) is a neurodevelopmental characterized by social communication difficulties and restricted repetitive behaviors or interests. Applied behavior analysis (ABA) has been shown to significantly improve outcomes for individuals on the autism spectrum. However, challenges regarding access, cost, provider shortages remain obstacles treatment delivery. To this end, parents were trained as parent technicians (pBTs), improving access ABA, empowering provide ABA in their...
LLMs have become increasingly capable at accomplishing a range of specialized-tasks and can be utilized to expand equitable access medical knowledge. Most involved extensive fine-tuning, leveraging specialized data significant, thus costly, amounts computational power. Many the top performing are proprietary their is limited very few research groups. However, open-source (OS) models represent key area growth for due significant improvements in performance an inherent ability provide...
Abstract Background Autism spectrum disorder (ASD) can have traits that impact multiple domains of functioning and quality life, which persevere throughout life. To mitigate the ASD on long-term trajectory an individual’s it is imperative to seek early adequate treatment via scientifically validated approaches, applied behavior analysis (ABA) gold standard. ABA must be delivered a technician with oversight from board-certified analyst. However, shortages in certified therapists create access...
<sec> <title>BACKGROUND</title> Acute respiratory distress syndrome (ARDS) is a condition that often considered to have broad and subjective diagnostic criteria associated with significant mortality morbidity. Early accurate prediction of ARDS related conditions such as hypoxemia sepsis could allow timely administration therapies, leading improved patient outcomes. </sec> <title>OBJECTIVE</title> The aim this study perform an exploration how multilabel classification in the clinical setting...
Timely recognition of sepsis in hospital patients increases the likelihood patient survival. The value alert systems clinical settings is diminished if these alerts are generated after clinically relevant times: clinician suspicion (clinical evaluation or treatment for sepsis) onset (defined by SOFA score). We evaluate and compare two models - standard early using traditional time-agnostic methods (area under curve: AUC; true positive rate: TPR) a time-dependent approach with redefined...
Abstract Background: Acute respiratory failure (ARF) presents within a spectrum of clinical manifestations and illness severity, mortality occurs in approximately 30% patients who develop ARF. Early risk identification is imperative for implementation prophylactic measures prior to ARF onset. In this study, we validate machine learning algorithm (MLA) predict at requiring advanced support. Methods: This retrospective study used data from 155,725 patient electronic health records obtained...
Construction of a decision tree is well researched problem in data mining.Mining streaming very useful and necessary application.Algorithms such as VFDT CVFDT are used for construction, but lot new examples added, optimal model needs to be constructed.Here this paper, we have provided an algorithm construction which uses discriminant analysis, select the cut point splitting tests, thus optimizing time complexity from O(nlogn) O(n).We also analyzed several learning strategies dynamic...
Abstract Importance: Despite sex and race disparities in the symptom presentation, diagnosis, management of acute coronary syndrome (ACS), these differences have not been investigated development validation machine learning (ML) models using individualized patient information from electronic health records (EHRs) to diagnose ACS. Objective: To evaluate ML-based ACS diagnosis performance across different subpopulations a multi-site emergency department (ED) setting determine how bias...