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MEDITE CANCER DIAGNOSTICS, INC.: accumulated depreciation on property, plant and equipment

Accumulated depreciation on property, plant and equipment for MEDITE CANCER DIAGNOSTICS, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All MEDITE CANCER DIAGNOSTICS, INC. financial histories

What this measure means

Cumulative depreciation, depletion and amortization recorded against property, plant and equipment. It measures cost allocation to date, not physical wear or market value.

Exact concept: us-gaap:AccumulatedDepreciationDepletionAndAmortizationPropertyPlantAndEquipment. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2011-12-31 to 2017-12-31. The SEC response was captured on 2026-09-22.

This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.

Selected filing history

Accumulated depreciation on property, plant and equipment in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
-2017-12-311,646,000USD2018-05-1710-K · 0001654954-18-005606 SEC
-2016-12-311,337,000USD2018-05-1710-K · 0001654954-18-005606 SEC
-2015-12-311,219,000USD2017-04-1410-K · 0001654954-17-003300 SEC
-2014-12-31999,000USD2016-04-1210-K · 0001415889-16-005503 SEC
-2013-12-31887,000USD2015-05-1110-K · 0001144204-15-029402 SEC
-2012-12-311,941,000USD2014-04-1410-K · 0001144204-14-022503 SEC
-2011-12-311,825,000USD2013-04-0110-K · 0001144204-13-019354 SEC

Related MEDITE CANCER DIAGNOSTICS, INC. histories

Inspect the source

Entity
MEDITE CANCER DIAGNOSTICS, INC. / CIK 0000075439
Captured
SEC response SHA-256
894bae5eb0c9f99e2d370f64d953b311646ca4f855ecd85dae9618e3eba4d078

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000075439.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))