OpenMedLM: prompt engineering can out-perform fine-tuning in medical question-answering with open-source large language models

J Maharjan, A Garikipati, NP Singh, L Cyrus… - Scientific Reports, 2024 - nature.com
LLMs can accomplish specialized medical knowledge tasks, however, equitable access is
hindered by the extensive fine-tuning, specialized medical data requirement, and limited …

Machine learning differentiation of autism spectrum sub-classifications

R Thapa, A Garikipati, M Ciobanu, NP Singh… - Journal of Autism and …, 2024 - Springer
Purpose Disorders on the autism spectrum have characteristics that can manifest as
difficulties with communication, executive functioning, daily living, and more. These …

Machine Learning Approach for Improved Longitudinal Prediction of Progression from Mild Cognitive Impairment to Alzheimer's Disease

RP Adelson, A Garikipati, J Maharjan, M Ciobanu… - Diagnostics, 2023 - mdpi.com
Mild cognitive impairment (MCI) is cognitive decline that can indicate future risk of
Alzheimer's disease (AD). We developed and validated a machine learning algorithm (MLA) …

Family-centric applied behavior analysis facilitates improved treatment utilization and outcomes

RP Adelson, M Ciobanu, A Garikipati… - Journal of Clinical …, 2024 - mdpi.com
Background/Objective: Autism spectrum disorder (ASD) is a neurodevelopmental condition
characterized by lifelong impacts on functional social and daily living skills, and restricted …

[HTML][HTML] Clinical outcomes of a hybrid model approach to applied behavioral analysis treatment

A Garikipati, M Ciobanu, NP Singh, G Barnes… - Cureus, 2023 - ncbi.nlm.nih.gov
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 …

Machine Learning Approach with Harmonized Multinational Datasets for Enhanced Prediction of Hypothyroidism in Patients with Type 2 Diabetes

RP Adelson, A Garikipati, Y Zhou, M Ciobanu… - Diagnostics, 2024 - mdpi.com
Type 2 diabetes (T2D) is a global health concern with increasing prevalence. Comorbid
hypothyroidism (HT) exacerbates kidney, cardiac, neurological and other complications of …

[HTML][HTML] Parent-Led Applied Behavior Analysis to Impact Clinical Outcomes for Individuals on the Autism Spectrum: Retrospective Chart Review

A Garikipati, M Ciobanu, NP Singh… - JMIR Pediatrics and …, 2024 - pediatrics.jmir.org
Background: Autism spectrum disorder (ASD) can have traits that impact multiple domains of
functioning and quality of life, which can persevere throughout life. To mitigate the impact of …

A Prediction Model of Autism Spectrum Diagnosis from Well-Baby Electronic Data Using Machine Learning

A Ben-Sasson, J Guedalia, L Nativ, K Ilan, M Shaham… - Children, 2024 - mdpi.com
Early detection of autism spectrum disorder (ASD) is crucial for timely intervention, yet
diagnosis typically occurs after age three. This study aimed to develop a machine learning …

Family-Centric Applied Behavior Analysis Promotes Sustained Treatment Utilization and Attainment of Patient Goals

RP Adelson, M Ciobanu, A Garikipati, NJ Castell… - Cureus, 2024 - pmc.ncbi.nlm.nih.gov
Background/objectives: Autism spectrum disorder (ASD) is a neurodevelopmental disorder
characterized by social communication difficulties and restricted repetitive behaviors or …

[PDF][PDF] A computational intelligent analysis of autism spectrum disorder using machine learning techniques

MA Mareeswaran, K Selvarajan - Int J Artif Intell, 2024 - researchgate.net
Children between the ages of 12 and 24 months who have autism spectrum disorder (ASD)
experience abnormalities in the brain that result in undesirable symptoms. Children with …