A device for determining an internal condition of a subject by analysis of an enclosed volume, the device comprising: a communication port configured to receive microwave scattering measurement data related to said enclosed volume; a processing unit configured to perform a mapping of the microwave scattering measurement data with respect to a training data set, wherein said training data set comprises microwave scattering data from test subjects that are known to be healthy, to calculate the weighting matrix, ψ, wherein said microwave scattering data from test subjects that are known to be healthy is a base space with a size of m +1 training samples which describes a normal variation in measurements from test subjects that are known to be healthy, whereby the distance, d, of each test point, x t, from a sample mean, x, of said m+1 training samples of said base space is written as: d = x t − x ̅ T Ψ x t − x ̅ 1 2 where the sample mean of said m+1 training samples of said base space is given by: x ̅ = 1 m + 1 ∑ i = 1 m + 1 x i whereby a sample data matrix, X, is given by: X = x 1 − x ̅ x 2 − x ̅... x m + 1 − x ̅ and each column of said sample data matrix comprises one sample of the base data centered around said sample mean, x, and a singular value decomposition of the sample data matrix, X is: X = USV T where U is an n -by- n orthonormal matrix whose columns form a set of orthogonal basis vectors for X, S is n -by- m +1 diagonal matrix that comprises the singular values of X on the diagonal, and V is an m+1-by-m+1 orthonormal matrix, whereby partitioning the factors gives: U = U ^ 1 U ^ 2 and S = 0 S ^ 1 ⋮ 0 ⋯ 0 S ^ 2 where Û 1 ∈ R n × m and Ŝ 1 ∈ R m × m represent the m first non-zero singular values and Ŝ 2 is a zero matrix, whereby for any data point x i from said base space there exists an α i ∈ R m such that x i = x ̅ + U ^ 1 α i where Û 1 is a basis that describes the space within the base data and varies around said sample mean, x, whereby any test point x t in the n -dimensional space may be decomposed as: x t = x ̅ + U ^ 1 α + U ^ 2 β where α ∈ R m and β ∈ R n-m, whereby the distance, d, between the test point x t and the sample mean x of said m+1 training samples of said base space is calculated by different choices of the weighting matrix ψ and the Subspace distance (d SD) in the space perpendicular of the base space or within a range close to 90° is utilized; whereby the test point x t and the sample mean x of said m+1 training samples of said base space are projected onto the base space and then the distance from the subspace is calculated, the processing unit further configured to estimate the internal condition based on the mapping wherein the Subspace distance (d SD) is indicative of deviations from healthy subjects. a communication port configured to receive microwave scattering measurement data related to said enclosed volume; a processing unit configured to perform a mapping of the microwave scattering measurement data with respect to a training data set, wherein said training data set comprises microwave scattering data from test subjects that are known to be healthy, to calculate the weighting matrix, ψ, wherein said microwave scattering data from test subjects that are known to be healthy is a base space with a size of m +1 training samples which describes a normal variation in measurements from test subjects that are known to be healthy, whereby the distance, d, of each test point, x t, from a sample mean, x, of said m+1 training samples of said base space is written as: d = x t − x ̅ T Ψ x t − x ̅ 1 2 where the sample mean of said m+1 training samples of said base space is given by: x ̅ = 1 m + 1 ∑ i = 1 m + 1 x i whereby a sample data matrix, X, is given by: X = x 1 − x ̅ x 2 − x ̅... x m + 1 − x ̅ and each column of said sample data matrix comprises one sample of the base data centered around said sample mean, x, and a singular value decomposition of the sample data matrix, X is: X = USV T where U is an n -by- n orthonormal matrix whose columns form a set of orthogonal basis vectors for X, S is n -by- m +1 diagonal matrix that comprises the singular values of X on the diagonal, and V is an m+1-by-m+1 orthonormal matrix, whereby partitioning the factors gives: U = U ^ 1 U ^ 2 and S = 0 S ^ 1 ⋮ 0 ⋯ 0 S ^ 2 where Û 1 ∈ R n × m and Ŝ 1 ∈ R m × m represent the m first non-zero singular values and Ŝ 2 is a zero matrix, whereby for any data point x i from said base space there exists an α i ∈ R m such that x i = x ̅ + U ^ 1 α i where Û 1 is a basis that describes the space within the base data and varies around said sample mean, x, whereby any test point x t in the n -dimensional space may be decomposed as: x t = x ̅ + U ^ 1 α + U ^ 2 β where α ∈ R m and β ∈ R n-m, whereby the distance, d, between the test point x t and the sample mean x of said m+1 training samples of said base space is calculated by different choices of the weighting matrix ψ and the Subspace distance (d SD) in the space perpendicular of the base space or within a range close to 90° is utilized; whereby the test point x t and the sample mean x of said m+1 training samples of said base space are projected onto the base space and then the distance from the subspace is calculated, the processing unit further configured to estimate the internal condition based on the mapping wherein the Subspace distance (d SD) is indicative of deviations from healthy subjects.