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SEE SCHEDULE O
Source: IRS Form 990 (Tax Year 2023)
Source: IRS Form 990 via ProPublica Nonprofit Explorer
Total Revenue
▼$5.7M
Total Contributions
$884.8K
Total Expenses
▼$5.2M
Total Assets
$3.8M
Total Liabilities
▼$589.8K
Net Assets
$3.2M
Officer Compensation
→$0
Other Salaries
$2M
Investment Income
▼$4,883
Fundraising
▼$0
Source: USAspending.gov · Searched by organization name
Total Federal Funding
$3M
Awards Found
4
Department of Health and Human Services
$2M
AUTOMATIC ORGAN SEGMENTATION TOOL FOR RADIATION TREATMENT PLANNING OF CANCERS
Department of Health and Human Services
$340K
IMPROVED DIAGNOSIS OF SHUNT MALFUNCTION WITH AUTOMATIC QUANTIFICATION OF VENTRICULAR SPACE - ABSTRACT HYDROCEPHALUS IS THE BUILDUP OF CEREBROSPINAL FLUID (CSF) IN THE CAVITIES (VENTRICLES) DEEP WITHIN THE BRAIN. THE MOST COMMON TREATMENT FOR HYDROCEPHALUS IS CSF DIVERSION VIA VENTRICULOPERITONEAL (VP) SHUNTING. OVER 30,000 VP SHUNTS ARE PLACED PER YEAR IN THE UNITED STATES BY SOME ESTIMATES. DESPITE HOW COMMONLY THIS SURGERY IS PERFORMED, THE COMPLICATION RATE HAS BEEN ESTIMATED AT ALMOST 24%, WITH ONE REPORT CITING A 22% RATE OF REVISION. NEARLY 50% OF PATIENTS ADMITTED WITH SHUNT RELATED ISSUES REQUIRE A STAY OF FIVE OR MORE DAYS. GIVEN THE RATE OF SURGICAL SITE INFECTIONS AND COMPLICATIONS ASSOCIATED WITH SHUNT EXPLORATIONS AND REVISIONS, ACCURATE DIAGNOSIS OF A SHUNT MALFUNCTION REMAINS A CRITICAL, IF ELUSIVE, GOAL FOR MANY NEUROSURGEONS. ONE OF THE DIFFICULTIES IN ESTABLISHING A DIAGNOSIS BASED ON IMAGING ALONE IS THE LACK OF STANDARDIZED ROBUST METHODS OF MEASURING VENTRICULAR SIZE. RECENTLY VOLUMETRIC ANALYSES HAVE BEEN STUDIED AS A METHOD FOR MEASURING VENTRICULAR SIZE, AS COMPARED TO THE EVANS’ INDEX OR FRONTAL-OCCIPITAL HORN RATIOS AND HAVE BEEN SUGGESTED IS MORE ACCURATE AND A BETTER TOOL FOR MEASURING RESPONSE OF VENTRICULAR SIZE TO SHUNTING. HOWEVER, THE ASSOCIATED HUMAN EFFORTS AND INTER- AND INTRA-OBSERVER VARIABILITY IN SEGMENTING THE VENTRICLES PROHIBITS ITS WIDE CLINICAL ADOPTION. THE OTHER DIFFICULTY WITH ESTABLISHING A DIAGNOSIS OF VENTRICULOMEGALY OR HYDROCEPHALUS, INVOLVES A LACK OF A STANDARDIZED, NORMATIVE DATASET WITH A RANGE OF WHAT IS CONSIDERED "NORMAL" FOR VARIOUS AGE RANGES AS THE VENTRICLE SIZE INCREASES WITH AGE. CURRENT LITERATURE LACKS A ROBUST NORMATIVE DATASET OF VENTRICULAR SIZE BY AGE AND GENDER AND ONLY RECENTLY HAS SUCH A DATASET BEEN PRODUCED FOR THE PEDIATRIC AGE RANGE. ESTABLISHMENT OF NORMATIVE VALUES FOR VENTRICULAR VOLUME AND MORPHOLOGY ACROSS ALL AGE POPULATION IS SORELY NEEDED AND WILL ALLOW FOR THE INVESTIGATION OF A VARIETY OF TOPICS RELATED TO HYDROCEPHALUS AND ULTIMATELY ASSISTING IN THE DETECTION AND TRIAGE OF HYDROCEPHALUS AND VP SHUNT RELATED COMPLICATIONS OR MALFUNCTIONS. IN RECENT YEARS, THE RAPID DEVELOPMENT OF DEEP LEARNING (DL) MODELS HAS LED TO GREAT IMPACT ON MANY AREAS OF MEDICINE, ESPECIALLY FOR AUTOMATIC IMAGE ANALYSIS TASKS INCLUDING SEGMENTATION. TAKING ADVANTAGE OF DL MODELS, TWO AIMS ARE PROPOSED IN THIS PROJECT: 1) DEVELOP AND VALIDATE A ROBUST DL MODEL FOR VENTRICLE SEGMENTATION INCLUDING MULTI-MODALITY SUPPORT AND AUTOMATIC FAILURE DETECTION AND BUILD A NORMATIVE DATABASE; 2) DEVELOP A SOFTWARE PROTOTYPE THAT INCORPORATES THE DL MODEL AND NORMATIVE VALUES AND FITS THE CLINICAL WORKFLOW FOR IMAGE-BASED DIAGNOSIS OF SHUNT MALFUNCTION. ULTIMATELY, A UNIQUE SOFTWARE PRODUCT WILL BE DEVELOPED AND COMMERCIALIZED TO IMPROVE THE DIAGNOSIS OF SHUNT MALFUNCTION AND HYDROCEPHALUS AND BENEFIT THE PATIENTS WITH BETTER SURGICAL OUTCOME AND REDUCED COST.
Department of Health and Human Services
$304.2K
DEVELOPMENT OF VALIDATION OF A NOVEL SOFTWARE PLATFORM FOR DECENTRALIZED CLINICAL TRIAL IN SUBSTANCE USE DISORDER INCORPORATING LARGE LANGUAGE MODELS - ABSTRACT SUBSTANCE USE DISORDER (SUD) CLINICAL TRIALS TRADITIONALLY PERFORM RECRUITMENT, ENROLLMENT, INTERVENTIONS, AS WELL AS INFORMATION COLLECTION AT THE CLINICAL TRIAL SITES. IN-PERSON VISITS AT THE SITES ARE USED FOR SCREENING, ASSIGNMENT TO INTERVENTIONS, TREATMENT, OR OTHER INTERVENTION, FOLLOW UP, AS WELL AS COLLECTION OF INFORMATION FROM PARTICIPANTS AND ENTERING IT IN A DATABASE. REQUIREMENTS FOR PARTICIPANTS TO BE PHYSICALLY PRESENT AT THE STUDY LOCATION MAY BE LIMITING THE DIVERSITY OF THE PARTICIPANTS IN THE TRIALS DUE TO A VARIETY OF FACTORS INCLUDING, FOR EXAMPLE, TIME TO TRAVEL TO THE CENTER, LOSS OF TIME FROM WORK, TRANSPORTATION ISSUES, CHILD, AND ELDER CARE RESPONSIBILITIES. THE PERCEPTION OF STIGMA ASSOCIATED WITH PARTICIPATING IN A SUD TRIAL CAN ALSO PREVENT PARTICIPATION. THESE FACTORS OFTEN HAMPER ENGAGEMENT, RECRUITMENT, SCREENING AS WELL AS RETENTION IN TRIALS. IN A SURVEY OF CLINICAL TRIALS PARTICIPANTS, IT WAS FOUND THAT THEY MOST OFTEN DISLIKE THE LOCATION, THE LENGTH OF THE VISIT AND TIME COMMITMENT. DECENTRALIZED CLINICAL TRIALS (DCTS) ALLOWS FOR MOST OF THE VISITS TO BE CONVERTED INTO TELEHEALTH VISITS AND/OR PHONE CALLS. THE MONITORING, WHEN NEEDED, IS DONE WITH EQUIPMENT DELIVERED TO THE PATIENT'S HOUSE OR AT LOCAL CLINICAL LABORATORIES AND/OR HEALTH CARE PROVIDERS. WEARABLE DEVICES HAVE DEMONSTRATED SUFFICIENT ACCURACY IN MANY MONITORING TASKS SUCH AS STEPS OR HEART RATES. THIS APPROACH MAY SOLVE THE COMMUTING PROBLEM AND DECREASE THE LOSS OF TIME FROM WORK AND HOME CARE ISSUES. HOWEVER, THERE ARE STILL GAPS THAT PREVENT THE UTILIZATION OF DCT IN SUD MAINLY DUE TO THE HETEROGENEITY OF THE DATA AND DIFFICULTY FOR THE CLINICAL TRIAL COORDINATORS TO GO THROUGH ALL PIECES OF THE DATA TO ENSURE THE ACCURACY OF EVERY ENTRY. CURRENT CLINICAL TRIAL PLATFORMS DO NOT OFFER A GOOD SUPPORT FOR DCTS IN SUD. ON ANOTHER END, THE DEVELOPMENT OF LARGE LANGUAGE MODELS (LLMS) HAS SHOWN SIGNIFICANT POTENTIAL TO FUNCTION LIKE A HUMAN IN NATURAL LANGUAGE PROCESSING (NLP) TASKS INCLUDING SEMATIC ANALYSIS AND TEXT GENERATION. BY FINETUNING AN EXISTING LLM WITH SPECIFIC KNOWLEDGE, SUCH AS SUD, IT CAN PERFORM BETTER AT THIS DOMAIN AND CAN POTENTIALLY AUTOMATE MANY COMMUNICATION AND DATA COLLECTION TASKS, WHICH ARE TRADITIONALLY PERFORMED BY HUMAN EXPERTS SUCH AS THE CLINICAL TRIAL COORDINATORS. IN THIS PROJECT, WE AIM TO DEVELOP AND VALIDATE A NOVEL SOFTWARE PLATFORM THAT WILL SPECIFICALLY SOLVE THE CHALLENGES IN DCT UNDER THE CONTEXT OF SUD AND LEVERAGE THE CUTTING-EDGE LLM TECHNOLOGY TO IMPROVE EFFICIENCY AND ACCURACY OF DATA COLLECTION. IN THE PHASE I PERIOD OF THIS PROJECT, WE AIM TO PERFORM FEASIBILITY TESTING WITH THE FOLLOWING TWO AIMS: 1) DEVELOP A NOVEL SOFTWARE PLATFORM FOR DCT IN SUD WITH FINE-TUNED LLM, 2) VALIDATE THE LLM ACCURACY AND SOFTWARE USABILITY IN AN EMULATED SUD TRIAL USING RETROSPECTIVE DATA. BY ADDRESSING THE TECHNICAL AND PRACTICAL CHALLENGES OF DCT AND LEVERAGING CUTTING-EDGE TECHNOLOGY, THIS PROJECT HAS THE POTENTIAL TO SHIFT THE CLINICAL PARADIGM FOR SUD CLINICAL TRIALS TO ENCOURAGE MORE PARTICIPANTS FROM ALL BACKGROUND AND LEAD TO IMPROVED SUD TREATMENTS FOR ALL PATIENT POPULATION.
Department of Health and Human Services
$299.3K
AUTOMATIC THORACIC ORGAN SEGMENTATION TOOL FOR RADIATION TREATMENT PLANNING OF CANCERS IN THORACIC REGION
Source: Federal Audit Clearinghouse (fac.gov)
No federal single audit records found for this organization.
Single audits are required for entities expending $750,000+ in federal awards annually.
Source: IRS e-Filed Form 990
No officer or director compensation data available for this organization.
This data is sourced from IRS Form 990, Part VII. It may not be available if the organization files Form 990-N (e-Postcard) or has not yet been enriched.
Source: IRS Publication 78, Auto-Revocation List & e-Postcard Data
Tax-deductible contributions: Yes
Deductibility code: PC
Sources: IRS e-Filed Form 990 (XML) & ProPublica Nonprofit Explorer
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| Year | Revenue | Contributions | Expenses | Assets | Net Assets |
|---|---|---|---|---|---|
| 2023 | $5.7M | $884.8K | $5.2M | $3.8M | $3.2M |
| 2022 | $5.3M | $1.9M | $4.6M | $3.6M | $2.8M |
| 2021 | $3.8M | $2M | $3.5M | $2.9M | $2.1M |
| 2020 | $2.9M | $1.7M | $2.9M | $2.4M | $1.9M |
Sources: ProPublica Nonprofit Explorer & IRS e-File Index
| Tax Year | Form Type | Source | Documents |
|---|---|---|---|
| 2024 | 990 | IRS e-File | PDF not yet published by IRSView Filing → |
| 2023 | 990 | DataIRS e-File | PDF not yet published by IRSView Filing → |
| 2022 | 990 | DataIRS e-File |
Financial data: IRS Form 990 via ProPublica Nonprofit Explorer (Tax Year 2023)
Federal grants: USAspending.gov (live)
Organization info: IRS Business Master File · ProPublica Nonprofit Explorer
Tax-deductibility: IRS Publication 78
| 2019 | $1.8M | $1.6M | $2M | $2.1M | $1.9M |
| 2018 | $1.6M | $1.6M | $588.6K | $2.2M | $2.1M |
| 2021 | 990 | Data | PDF not yet published by IRS |
| 2020 | 990 | Data | PDF not yet published by IRS |
| 2019 | 990 | Data |
| 2018 | 990 | Data |