Machine Learning For Healthcare
| Fiscal year | Revenue | Expenses | Net | Reserve mo. | Staff % |
|---|---|---|---|---|---|
| 2017 | 90,300 | 52,104 | 38,196 | 8.8 | 0% |
| 2018 | 139,535 | 96,558 | 42,977 | 9.4 | 0% |
| 2019 | 134,915 | 89,551 | 45,364 | 14.0 | 0% |
| 2020 | 38,625 | 24,833 | 13,792 | 57.2 | 0% |
| 2021 | 30,441 | 27,389 | 3,052 | 53.2 | — |
| 2022 | 97,844 | 86,900 | 10,944 | 18.3 | — |
| 2023 | 117,896 | 179,236 | −61,340 | 4.8 | — |
In its most recent public year (2023), this organization spent $61,340 more than it brought in. Its reserves stood at about 4.8 months of spending, down from 8.8 in 2017.
Reserve months = net assets ÷ average monthly spending; net assets count everything the organization owns beyond its debts — buildings and donor-restricted funds included, not just cash. Staff pay = salaries, wages, and officer compensation; it excludes benefits and payroll taxes. The IRS releases this data years after the fact — this organization's newest public year is 2023. Years refer to the calendar year in which the organization's fiscal year ended. Short-form filers do not publicly report donor-restricted balances or staffing costs. Source filings
Machine Learning For Healthcare's IRS filings as a feed — one entry per filing year, through 2023. Add the address to any feed reader; in Slack, send /feed subscribe with it (pasting the link alone won't subscribe). How this feed works