How should I practice Filter Paginated Medical Records?

Start by reading the full statement, solve the visible examples, then compare the pattern against related NVIDIA phone screen problems in FastPrep.

Is Filter Paginated Medical Records associated with NVIDIA?

FastPrep tags this as a NVIDIA phone screen coding practice problem when the problem catalog has that company and stage context.

Filter Paginated Medical Records

NVIDIA● MediumFULLTIMEPHONE SCREEN

Learn

Problem statement

Filter a paginated collection of synthetic medical records using ordinary comparisons and the average of historical weight measurements.

Finite page adapter

For this exercise, assume records concatenates all fetched pages in page order. Each full page has ten records; the final page may be shorter. Rows 0..9 form the first page, rows 10..19 form the second, and so on. An empty array represents no records. No network request is needed in this finite adapter.

Each row is [recordId, age]. All record IDs are unique. Each weightHistory row is [recordId, weight] and contributes one historical measurement, including repeated equal measurements. History rows may be interleaved and unordered; every referenced ID occurs in records.

For this exercise, assume a record qualifies exactly when all conditions hold:

Its age is between minAge and maxAge, inclusive.
It has at least one historical weight measurement.
The arithmetic mean of all its historical weights is between minAverageWeight and maxAverageWeight, inclusive.

Use the exact unrounded mean. All weights and weight bounds use the same arbitrary integer unit. Return the IDs of qualifying records in their original page-and-row order. An empty result is allowed. Age fields, threshold ranges, missing-history handling and this output shape are practice definitions, not recovered original requirements.

Function

filterMedicalRecords(records: int[][], weightHistory: int[][], minAge: int, maxAge: int, minAverageWeight: int, maxAverageWeight: int) → int[]

Examples

Example 1

records = [[1,25],[2,40],[3,30]]weightHistory = [[1,60],[1,80],[2,65],[3,90]]minAge = 20maxAge = 35minAverageWeight = 65maxAverageWeight = 85return = [1]

Record1 has age25 and mean70. Record2 fails age; record3 fails average weight.

Example 2

records = [[1,30],[2,30],[3,30],[4,30],[5,30],[6,30],[7,30],[8,30],[9,30],[10,30],[11,30]]weightHistory = [[11,75]]minAge = 20maxAge = 40minAverageWeight = 70maxAverageWeight = 80return = [11]

Only record11 has history; it is on the second page and qualifies.

Example 3

records = []weightHistory = []minAge = 0maxAge = 120minAverageWeight = 0maxAverageWeight = 10000000return = []

An empty concatenation of pages has no qualifying records.

Constraints

0 <= records.length <= 256 and 0 <= weightHistory.length <= 512.
Every row in either matrix has exactly two integers.
Record IDs are distinct integers from 1 through 10^9; every history ID belongs to one record.
0 <= age <= 120 and 1 <= weight <= 10^7.
0 <= minAge <= maxAge <= 120.
0 <= minAverageWeight <= maxAverageWeight <= 10^7.
Sums and threshold products may exceed signed32-bit range; signed64-bit arithmetic is sufficient.